The skill advertises ScrapeCreators as offering "10,000 free API calls" in
six places. The actual free tier on the ScrapeCreators pricing page is
"100 credits free · No credit card required · Credits never expire" — a
100x overstatement that surprises users on signup.
Reporter (#367) burned through their full free allocation on a single
/last30days run after taking the 10,000-call claim at face value. They
verified the actual tier directly against scrapecreators.com plus an
independent review at fahimai.com.
Sweep:
- hooks/scripts/check-config.sh:110 (SessionStart hook tip line)
- README.md:228 (Sources × Cost table row)
- HERMES_SETUP.md:62 (Optional: ScrapeCreators bullet)
- skills/last30days/scripts/lib/ui.py:199 (PROMO_SINGLE_KEY["reddit"])
- skills/last30days/SKILL.md:1648 ("PAYG after 10,000 free API calls")
- skills/last30days/SKILL.md:1661 ("10,000 free API calls, then PAYG")
Wording defaults to the provider's own framing — "100 free credits" — and
keeps PAYG language where it was already explicit, since the paid step is
the part users were actually getting blindsided by.
CI gates: tests/test_plugin_contract.py (4) + tests/test_version_consistency.py (4)
all pass. shellcheck clean. No tests pin the "10,000" string.
Two related drifts surfaced while reviewing PR #399 (EXCLUDE_SOURCES) —
docs claimed several SC-backed sources required INCLUDE_SOURCES opt-in
that the code didn't actually enforce, and threads was inconsistently
gated relative to its same-key siblings.
This commit picks the "code as source of truth + EXCLUDE_SOURCES as
suppression knob" model and aligns docs to match. It also promotes
threads to the same auto-on tier as tiktok and instagram, since all
three share the SC key and per-call cost shape — there was no real
product reason for threads being opt-in while the other two weren't.
The resulting source-gating model is three-tier and intentional:
• **Auto-on if backing infra present** (suppress via EXCLUDE_SOURCES):
reddit, HN, polymarket, X, youtube, github, bluesky, truthsocial,
grounding, **tiktok, instagram, threads**
• **INCLUDE_SOURCES persistent opt-in** (cost/billing reasons):
perplexity (different paid API — OpenRouter),
tiktok_comments / youtube_comments (N× extra SC calls per video)
• **--search per-query opt-in** (relevance reasons):
pinterest (visual pins, narrow utility),
xiaohongshu (Chinese-market specific)
Changes:
- env.py: `is_threads_available()` drops the INCLUDE_SOURCES check,
now mirrors tiktok/instagram (SC key → True). Docstring updated.
- tests/test_env_v3.py: new `ThreadsAvailabilityTests` class locks in
the new contract and includes a regression guard ("INCLUDE_SOURCES
should not be needed").
- SKILL.md: lines 333-338 rewritten so the model's "Build
ACTIVE_SOURCES_LIST" checklist reflects what the engine actually
runs. Drops false INCLUDE_SOURCES requirement for
tiktok/instagram/threads; corrects pinterest to mention --search;
adds missing INCLUDE_SOURCES=perplexity requirement.
- README: same alignment for the user-facing "Everything else in v3"
section.
Note on EXCLUDE_SOURCES references in the new docs: the suppression
flag is wired up in PR #399. SKILL.md and README mention EXCLUDE_SOURCES
as the opt-out path; that prose is forward-looking until #399 lands.
The behavior changes in this PR (threads auto-on) are self-contained
and don't require #399 to function — but for users who want to suppress
the newly-auto-on threads source, #399 needs to land first.
Adds the macOS Keychain as the lowest-priority credential source on Darwin.
Items stored as generic passwords with service name "last30days-<KEY>" for
the current user are picked up automatically by get_config() — file env
and process env still win on collision.
No new config knob: behavior is strictly additive. On non-Darwin (or when
the `security` binary is missing) the loader is a no-op, so Linux/Windows
behavior is unchanged.
Priority (highest wins):
1. Environment variables
2. .claude/last30days.env (per-project)
3. ~/.config/last30days/.env (global)
4. macOS Keychain items prefixed last30days- (new)
Includes:
- lib/env.py: KEYCHAIN_SERVICE_PREFIX constant, _load_keychain helper
(platform-gated, shutil.which-gated, subprocess-error tolerant),
wiring into get_config before get_openai_auth so OPENAI_API_KEY can
come from Keychain too, _CONFIG_SOURCE reports "keychain" when no
file source is present.
- scripts/setup-keychain.sh: bash helper with interactive set,
--list, --delete, --replace modes. Uses `security add-generic-password`.
- tests/test_env_keychain.py: 12 tests covering platform gate,
missing-binary gate, success path, whitespace stripping, subprocess
errors swallowed, get_config precedence, and an OPENAI_AUTH wiring
regression test.
- tests/test_env_cookies.py: existing integration test mocks the new
_load_keychain hook so it stays hermetic on Darwin developer
machines that have real keychain entries.
- README.md: new "macOS Keychain (optional)" subsection under
"Bring your own keys" documenting setup-keychain.sh and the manual
`security add-generic-password` invocation.
Tested on macOS with a populated keychain and against the existing pytest
suite — CI-tracked tests (test_plugin_contract.py, test_version_consistency.py)
plus all env-touching tests pass. Pre-existing unrelated failures in
test_store.py / test_watchlist_commands.py / test_setup_openclaw.py /
test_footer_nudge_suppression.py are untouched.
`npx skills add` defaults to project-local install (`./.skills/`,
committed with the repo). For a research-the-world skill like this one,
that's almost never what users want — they want it available across all
projects, not scoped to whichever directory they happened to run the
install from.
Adding `-g` (global) to every npx skills example in the README:
- Top-of-file install snippet
- Install table row
- Claude Code subsection's "alternative via npx skills" example
- Codex/Cursor/etc. subsection's default, per-harness, update, list,
and remove commands
Brief one-liner explains what `-g` does and notes that dropping it
gives a project-local install for users who want team consistency on
a specific codebase.
The native `gemini extensions install` path was a workaround for the
v0.9.0 installer bug (still unresolved per upstream issue #11452).
Now that `npx skills add -a gemini-cli` covers Gemini cleanly with the
same install/update story as every other supported harness, the native
path is just one more confusing option to maintain. Users on Gemini get
the same recommendation everyone else does.
Removes the dedicated "Gemini CLI (native extension)" subsection and
the separate table row. Gemini CLI is now surfaced once, in the npx
skills section, alongside Codex, Cursor, Copilot, and the rest.
npx skills supports 50+ harnesses via the -a flag, including gemini-cli,
github-copilot, windsurf, cline, continue, roo, aider-desk, opencode,
goose, and more — not just the few I'd listed initially. Updating to
reflect that breadth.
- Top-of-file snippet now reads "Codex, Cursor, Copilot, Gemini CLI, or
any of 50+ Agent Skills hosts" (was: "Codex, Cursor, Copilot, or any
Agent Skills host" + Gemini listed separately in the table footer).
- Install table: same expansion; Gemini CLI native-extension row relabeled
to clarify it's the native path (not the only Gemini option).
- npx skills subsection: lists the most common harness flags and links
to the upstream vercel-labs/skills repo for the full list.
- Gemini CLI native subsection: now leads with "the npx skills path
above is simpler" and frames the native install as the alternative
for users with an existing Gemini extensions workflow or who hit
the v0.9.0 installer bug.
The skill is now installable across every major agent harness after the
SKILL.md path-resolver work landed in PR #400 + #404. README didn't yet
reflect that — the install table only listed Claude Code, OpenClaw, and
Gemini CLI, and the top-of-file install snippets featured Hermes (an
internal dev workflow, not a public install method).
Restructured the install section:
- Top-of-file snippets: just Claude Code (recommended, auto-updates) and
the universal `npx skills add` one-liner. Dropped Hermes from the
prominent spot (internal-only); pointed everything else to the Install
section below.
- Install table: added a third column for update commands, since every
harness now has a distinct update path worth surfacing. Added the
`npx skills` row covering Codex/Cursor/Copilot/any Agent Skills host.
- Claude Code subsection: explains why it's recommended (marketplace
handles versioned cache + auto-refresh) and notes that the agent-skills
install also works on Claude Code if preferred (`-a claude-code`).
- New "Codex, Cursor, Copilot, and other Agent Skills hosts" subsection:
shows the default install, per-harness `-a` targeting, and the update
commands (`npx skills update last30days` for one skill, bare
`npx skills update` for all).
- Manual (developer) subsection: switched from a clone-into-skills-dir
recipe to a clone + symlink recipe. Symlink keeps the install in sync
with the working tree as you edit, no re-copy on each change.
No code changes. No version bump (docs-only).
* feat(digg): bump POSTS_PER_CLUSTER to 5 and render limit to 3
Match the per-item enrichment cap and inline-display cap used by the
other sources (Reddit, HN, YouTube, TikTok, GitHub all use 5 fetched /
3 displayed). At the previous 3/2 caps the engine routinely truncated
cluster context — a recent run on cli-printing-press lost the Jason
Calacanis quote tweet entirely because the display cut off after Garry
Tan's first two posts.
* feat(digg): rename 'Digg AI 1000' to 'Digg' in user-facing strings
Drop the 'AI 1000' suffix from the footer line, source label, inline
quote attribution ('via Digg'), why_relevant, container, mock title,
SKILL.md source list, and README sources table. Internal code comments
and docstrings still reference the upstream Digg AI 1000 product.
Bumps version to 3.2.1 and adds a CHANGELOG entry covering this rename
and the POSTS_PER_CLUSTER / render-limit bumps from the prior commit.
---------
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
* feat(digg): add Digg AI 1000 source module with cluster search and post enrichment
- search_digg shells out to digg-pp-cli with --since 30d --agent
- parse_digg_response normalizes clusters to last30days dict shape
- enrich_with_top_posts attaches top-ranked X posts to top-K clusters
- shutil.which gate plus subproc.run_with_timeout discipline matches
bird_x.py / youtube_yt.py patterns
25 unit tests cover parse, age window, relevance, binary-missing
fallback, timeout recovery, and partial enrichment failures.
* feat(digg): wire Digg source into pipeline, normalize, signals, and render
pipeline.py:
- Import digg, add to MOCK_AVAILABLE_SOURCES, gate via shutil.which
- Dispatch case calls search_digg + parse_digg_response, runs
enrich_with_top_posts at default/deep depth
- Mock fixture includes one enriched cluster + one bare cluster
normalize.py:
- _normalize_digg maps cluster dicts to SourceItem with
container='Digg AI 1000' and metadata.posts pass-through
signals.py:
- SOURCE_QUALITY['digg'] = 0.85 (top tier alongside YouTube,
reflecting Digg's curatorial layer)
- ENGAGEMENT_WEIGHTS['digg'] balances postCount, uniqueAuthors,
and the rank_score derived from Digg's curatorial position
render.py:
- SOURCE_LABELS['digg'] = 'Digg AI 1000'
- _FOOTER_SOURCES adds '⛏️ Digg AI 1000' line after GitHub
- ENGAGEMENT_DISPLAY mirrors footer keys
- New _digg_posts_for + _format_digg_quote helpers emit inline
'@handle via Digg AI 1000' quotes for clusters with attached X
posts; both compact and full-dump renderers call them
* feat(digg): polish per-item engagement display and progress label
- ENGAGEMENT_DISPLAY for digg uses 'posts' / 'auth' to match the
codebase abbreviation convention (HN: 'pts'/'cmt', X: 'rt'/'re')
- Footer item word changes from 'story' to 'cluster' to dodge the
pre-existing naive plural in _footer_line_for_source ('storys')
and to match Digg's actual data model
- ui.py SOURCE_COMPLETION_META adds digg with correct 'cluster'/
'clusters' plural so 'Research complete' shows 'Digg: N clusters'
* feat(digg): document Digg AI 1000 source in skill, README, and changelog
- planner.py SOURCE_CAPABILITIES adds digg with discussion/social/link
capabilities so the planner offers it through the standard fanout
- SKILL.md ACTIVE_SOURCES_LIST gate includes 'which digg-pp-cli' check
and the source list / available-sources line names digg as opt-in
- README.md Sources table adds the Digg AI 1000 row with the activation
gate so first-time readers see what they get
- CHANGELOG.md Unreleased section calls out the source addition
* fix(digg): enrich post-dedupe so brief survivors carry inline quotes
Pipeline dispatch was attaching X posts to the top-3 items returned by
search, but dedupe later picked different survivors when multiple
clusters compared similar (common for trending topics). The brief
ended up showing clusters with no posts attached even though
enrichment ran successfully on positions 0-2.
Move enrichment to _finalize_items_by_source. The new
digg.enrich_source_items helper reads metadata['clusterUrlId'] and
writes metadata['posts'] in place on the SourceItems that actually
survive dedupe.
Verified live on 'openclaw': 2 surviving clusters, both now carry
real X-post quotes from @sama and @jeremyphoward attributed
'via Digg AI 1000'.
Adds 3 unit tests covering survivor enrichment, non-digg skip, and
clusterUrlId fallback to item_id.
* test(digg): relax live off-topic test to check shape, not emptiness
Digg's live search uses fuzzy/popularity fallback, so an impossible
token can still return some loosely-related clusters. The contract
the pipeline depends on is shape (results is always a list);
token-overlap relevance handles the noise downstream.
---------
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Adds a one-command shareable HTML mode to /last30days. The skill detects
HTML intent (explicit --emit=html / --emit:html / --html flag in
$ARGUMENTS, or natural-language asks like "give me a shareable brief",
"for Slack", "export as HTML"), runs the normal research + chat synthesis
flow, then saves a self-contained HTML file to
~/Documents/Last30Days/{topic}-brief.html. The synthesis appears in chat
as usual; the HTML is an additional artifact for sharing.
User experience:
/last30days OpenClaw --emit=html
/last30days OpenClaw, give me an HTML brief for Slack
Synthesis prints to chat. Last line of the response: "📎 Shareable brief
saved to ~/Documents/Last30Days/openclaw-brief.html". Open it, drag it
into a message, browser-print to PDF, email it.
Architecture:
- SKILL.md gets a small detection block (triggers + early exit +
MUST/MUST NOT rules + rationale) that points to a reference file.
- references/save-html-brief.md owns the implementation: capture the
synthesis verbatim into a temp file via heredoc, invoke the engine
with --emit=html --synthesis-file, save to disk, append the
confirmation line to chat.
- lib/render.py exposes render_for_html(report, synthesis_md=None) and
render_for_html_comparison(...) -- clean markdown for HTML
conversion. Omits debug file header, model-facing safety note, and
data quality warnings (those stay in engine stderr; recipients can't
act on them in a shared artifact).
- lib/html_render.py is a new module: ~200-line CSS template (dark
mode default, prefers-color-scheme switch, print stylesheet, mobile
breakpoint), stdlib-regex markdown-to-HTML converter, marker-based
META + engine-footer wrapping, PROSE_LABELS registry promoting plain
-text labels to <h2>, colophon builder.
- last30days.py adds --emit=html argparse choice and --synthesis-file
PATH flag (engine still callable directly without the skill in the
loop).
Design:
- Voice-led research brief, not corporate report. Inter + JetBrains
Mono via Google Fonts with full system fallbacks (no FOIT, works
offline). Brand purple #a855f7 (#7c3aed in light mode). Type ramp:
body 17px/400/muted, bold lead-in 17px/600/fg, h2 + .prose-label
20px/600/fg, monospace badge/meta/footer/colophon at 13-13.5px.
- 720px max-width, generous whitespace, no card layouts or shadows.
- Print stylesheet: light theme, A4 margins, [href]::after URL
footnotes, page-break-inside:avoid on the engine footer.
Templated (locked) shell:
- HTML5 boilerplate, Google Fonts <link> with preconnect, all CSS
inline.
- .badge / .meta / .engine-footer / .colophon containers.
Flexible (role-based):
- <h2> rendering covers BOTH plain ## headers (comparison mode per
LAW 4 exception) AND promoted prose labels via PROSE_LABELS
registry. Adding a new SKILL.md prose label is a one-line tuple
addition; no CSS or template changes.
- Marker-based engine boundaries (<!-- META: ... -->,
<!-- PASS-THROUGH FOOTER -->) survive the markdown converter and
get promoted post-conversion. Robust to engine output format
changes.
- Generic markdown-to-HTML for body content; future SKILL.md additions
(new sections, tables, blockquotes) render correctly without code
changes.
Tests: 30 new tests in tests/test_html_render.py covering snapshots
(rich/thin/comparison), CLI parsing, --synthesis-file end-to-end, prose
label promotion, warning exclusion from artifact, parseability via
html.parser, no-script self-containment.
No SKILL.md voice contract changes, no LAWs 1-8 changes, no new pip
dependencies, no JavaScript anywhere.
* feat: vs mode runs N full passes; --competitors wraps vs with auto-discovery
Unifies vs-mode and --competitors onto one fanout architecture. A topic
containing "vs" / "versus" now runs N full pipeline.run() calls in parallel
(reverting the one-pass latency optimization that removed per-entity
depth); --competitors becomes a SKILL.md-level shortcut where the hosting
reasoning model (Claude Code, Codex, Hermes, Gemini) discovers N peers via
its own WebSearch, runs Step 0.55 per entity, and invokes the engine with
a vs-topic + --competitors-plan JSON.
Changed:
- vs-mode: N full passes in parallel via fanout (was 1 merged pass).
- --competitors: SKILL.md shortcut for vs-mode-with-discovery. Engine flag
kept for headless/cron use. LAW 7-style stderr reframed to lead with the
hosting-model path (use WebSearch + --competitors-plan) instead of
BRAVE_API_KEY. Footer BRAVE/SERPER nudge suppressed when --plan or
--competitors-plan present (hosting model already has WebSearch).
Added:
- --competitors-plan JSON flag: per-entity {x_handle, x_related, subreddits,
github_user, github_repos, context}. Accepts inline JSON or file path.
subrun_kwargs_for helper is the single source of truth for per-entity
kwargs — no closure-default fallthrough from main scope.
- Per-entity save files: each entity's sub-run produces its own
{slug}-raw.md with a single-row Resolved Entities block.
- --polymarket-keywords filter for ambiguous single-token topics.
Fixed:
- test_competitor_subrun_isolation regression suite locks in 3.0.12's
no-leak invariant (main flags do not inherit into peer sub-runs).
- Updates test_regression.py for the new comparison-mode payload shape.
Bumps plugin.json to 3.0.13. 1,219 tests passing.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix: comparison title attribution — (Last 30 Days) → (/Last30Days)
User feedback on 3.0.13 dogfood runs (Kanye vs Drake, Mercer Island,
Figma): the comparison-mode synthesis title should attribute to the
slash command rather than restate the date range.
Three SKILL.md occurrences updated. Pure documentation change. Bumps to
3.0.14.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Four fixes based on 2026-04-22 test-window feedback on v3.0.11 --competitors:
- Each competitor sub-run now runs Step 0.55 (X handle / subreddits /
GitHub) via resolve.auto_resolve inside the fanout closure. Deep-copied
config per entity prevents _auto_resolve_context leak across sub-runs.
Resolved data stored on report.artifacts["resolved"] for the renderer.
- New internal_subrun keyword on planner.plan_query and pipeline.run
suppresses the LAW 7 "No --plan passed" stderr for engine-internal
fan-out only. Default path unchanged.
- Default --competitors count is now 2 (3-way total). --competitors=N
still customizes; range 1..6.
- SKILL.md STEP 0 canonical-path self-check forces readers who loaded
from marketplaces/ (auto-restored to origin/main, stale) to re-read
from plugins/cache/last30days-skill/last30days/{VERSION}/SKILL.md.
Two of three 2026-04-22 test windows hit this stale-path trap.
- New ## Resolved Entities block in render_comparison_multi shows
per-entity handles/subs/github for debug visibility.
Bumps plugin.json to 3.0.12. 12 new tests; 1,175 total passing.
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Pass `--competitors` on a single-entity topic and the engine auto-discovers
2-6 peer entities via web search, runs the full pipeline on each in
parallel, and returns one N-way comparison reusing the existing 9-axis
Head-to-Head scaffold. `last30days OpenAI --competitors` resolves to
Anthropic + xAI + Google Gemini; `last30days Kanye West --competitors`
resolves to Drake + Kendrick Lamar + one more peer.
- New CLI flags: --competitors, --competitors=N, --competitors-list
- New scripts/lib/competitors.py — mirrors resolve.auto_resolve pattern
(web search + deterministic text extraction, no internal LLM)
- New scripts/lib/fanout.py — ThreadPoolExecutor orchestrator; per-entity
failures degrade gracefully as long as >=2 entities survive
- Multi-report render in scripts/lib/render.py reuses the comparison
scaffold for the synthesis table
- LAW 7-style stderr when no backend and no list, pointing the hosting
reasoning model at --competitors-list
- 38 new tests across CLI parsing, discovery, fanout, and rendering
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(normalize): pass YouTube top_comments through with Reddit-compatible shape
_normalize_youtube silently dropped top_comments after enrich_with_comments
populated them, so the downstream signals/render/entity layers never saw
YouTube comments. Map likes->score and text->excerpt so the existing
Reddit-compatible readers Just Work.
Shared _remap_comments helper will be reused for TikTok in a later commit.
* feat(tiktok): fetch top comments via ScrapeCreators when opted in
Mirrors the youtube_comments pattern: new env.is_tiktok_comments_available
gate (requires SCRAPECREATORS_API_KEY + tiktok_comments in INCLUDE_SOURCES),
tiktok.enrich_with_comments ranks posts and fetches via
GET /v1/tiktok/video/comments. Vote field is digg_count; text and user.nickname
come across verbatim. Pipeline calls the enricher right after TikTok search
when the gate is open.
Comment-fetch errors never crash the pipeline — the enricher returns an
empty list on 4xx/5xx.
* feat(normalize): pass TikTok top_comments through with digg_count->score mapping
Instagram uses the same shortform normalizer and has no comment fetcher
today, so the key is harmlessly absent there — no Instagram regression.
* feat(signals): add YouTube + TikTok top-comment score to engagement formula
Mirrors Reddit's 10% top-comment slot. Without top_comments present, the
formula reduces to views-dominant weighting; with a high-signal comment,
the item gets a meaningful bump (log1p(10k) ~ 9.2, weighted 0.10 = ~0.92
on the engagement score).
Updated the existing dominant-weight and missing-fields tests to the new
weights (0.45/0.32/0.13 for YT, 0.45/0.27/0.18 for TT). Views still dominate.
* feat(render): source-aware thresholds and vote labels for top comments
10 upvotes on Reddit signals community interest; 10 likes on a viral
TikTok is noise. Introduce per-source minimums (reddit 10, youtube 50,
tiktok 500) and native vote labels ('upvotes' for Reddit, 'likes' for
YT/TT). First-pass numbers — tune after live observation.
* docs: generalize top-comment quoting to YouTube + TikTok, add tiktok_comments opt-in
Synthesis instructions previously called out Reddit top comments only.
Now cover Reddit/YouTube/TikTok uniformly with source-appropriate vote
labels (upvotes vs likes), and explicitly frame YT transcript highlights
and comments as complementary signals. README and setup-wizard copy
document the new tiktok_comments INCLUDE_SOURCES token.
---------
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
- install matrix now leads with claude.ai (widest audience, one-click path)
- direct download link to GitHub release's 'latest' asset URL
- 3-step UI walkthrough with link to Settings > Capabilities > Skills
- Claude Code / OpenClaw / Gemini / manual paths still documented, collapsed
- removes the bash scripts/build-skill.sh requirement from end-user flow
Two SKILL.md files declared `name: last30days` with `user-invocable: true`,
which caused strict marketplace validators to reject the plugin with "Some
plugins in this marketplace have validation errors":
- ./SKILL.md (canonical, also reachable via skills/last30days-nux/ symlink)
- ./skills/last30days/SKILL.md (v3 architecture spec, real file)
In v2.9.6, skills/last30days/SKILL.md was a symlink to ../../SKILL.md so
only one skill existed. Commit 0a9ff16 (v3.0.0) added a new real file at
skills/last30days-v3/SKILL.md, and commit 9be0780 then renamed that
directory to skills/last30days/, replacing the original symlink with a
different real file. The collision has been live since v3.0.0 shipped.
This change:
- Renames skills/last30days/SKILL.md to name: last30days-v3-spec and sets
user-invocable: false. The file stays in place as internal architecture
documentation, but it no longer competes with the canonical skill.
- Fixes README.md link that pointed to the deleted skills/last30days-v3/
path (left over from the rename).
- Removes a stale variants/open/SKILL.md reference (variants/open was
deleted in v3.0.0).
After the change, only one canonical name=last30days user-invocable=true
skill exists (the root SKILL.md, also reachable via the
skills/last30days-nux/ symlink, same inode).
Closes#204.
This contribution was developed with AI assistance (Codex).
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Update README, launch copy, and UI guidance to prefer popup-free AUTH_TOKEN/CT0 configuration, and keep X backend selection on the verified Bird or xAI paths.
Validation: uv run python -m unittest tests.test_env_project
Mastodon-compatible API at truthsocial.com/api/v2/search.
Opt-in via TRUTHSOCIAL_TOKEN env var (bearer token from browser).
Silent when unconfigured. Full pipeline: search, parse, normalize,
score, dedupe, render across all 10 pipeline files.
27 new tests, 440 total passing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Fix plugin.json hooks field from invalid array to empty object
- Add Claude Code plugin install above ClawHub badge
- Version bump to v2.9.5 with new features block (Bluesky, comparative
mode, ScrapeCreators X, per-project env, expanded tests)
- Add Bluesky to all source list references
- Document BSKY_HANDLE/BSKY_APP_PASSWORD env vars in install + optional sections
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Update .claude-plugin/marketplace.json and plugin.json to v2.9.5 with
full metadata. Add plugin install instructions to README as the
recommended install method. The repo root serves as both the marketplace
and the plugin - skills/last30days/SKILL.md (symlink) is discovered
automatically.
Users can now install with:
/plugin marketplace add mvanhorn/last30days-skill
/plugin install last30days@last30days-skill
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add gemini-extension.json manifest with correct array-format settings,
symlink skills/last30days/SKILL.md to root SKILL.md for Gemini skill
discovery, add Gemini install paths to bash for-loop in both main and
open variant, and add Gemini CLI install instructions to README.
Incorporates the good parts of PR #53 (manifest, paths, README) while
avoiding duplicate SKILL.md, tool name scattering, and allowed-tools
pollution that would have created maintenance issues.
Closes#45
Co-Authored-By: Alex Ferrari <alex@thealexferrari.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Sync from public repo. Every run now saves the complete briefing as a
topic-named .md file to ~/Documents/Last30Days/. Credit @devin_explores.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add Instagram Reels as the 8th research source via ScrapeCreators API.
One API key (SCRAPECREATORS_API_KEY) now covers both TikTok and Instagram.
- Add scripts/lib/instagram.py: keyword search, transcript extraction,
relevance scoring, engagement metrics (views, likes, comments)
- Add InstagramItem to schema, normalization, scoring, dedup, rendering
- Add Instagram to orchestrator pipeline, watchlist, and UI spinners
- Update SKILL.md: stats template, citation priority, item format,
URL-to-name extraction rules, anti-Sources instruction
- Update README and CHANGELOG for v2.8
- Fix: Instagram/TikTok not running in --search= web-only path
- Fix: web stats line showing full URLs instead of domain names
- Replace APIFY_API_TOKEN with SCRAPECREATORS_API_KEY throughout
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace all Apify references with ScrapeCreators. Key points:
- No subscription required (was $5/mo with Apify)
- 100 free credits, pay-as-you-go after
- SCRAPECREATORS_API_KEY replaces APIFY_API_TOKEN
- Backwards compatible: APIFY_API_TOKEN still works as fallback
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add TikTok as 7th source throughout README: new V2.7 banner, real
search examples (Iran Israel: 61.6M views, Leah Halton: 152.6M views),
APIFY_API_TOKEN in installation, Apify in security table, fix stale
"six sources" references to "seven sources".
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: fix YAML error in argument-hint
* add codex auth support to responses API
* Use gpt-5.1-codex-mini as default model for Codex auth
Add CODEX_FALLBACK_MODELS chain (gpt-5.1-codex-mini → gpt-5.2) for
Codex endpoint which doesn't support standard OpenAI models like
gpt-4o-mini. Adds model fallback retry on 400 errors in the Codex
search path. Also adds test_codex_auth.py with 22 unit tests covering
JWT decoding, auth resolution, SSE parsing, and payload building.
* Pass .env credentials to Bird Node subprocesses for X auth
On platforms without browser cookie access (e.g. WSL2), Bird's
vendored Node.js module cannot read AUTH_TOKEN/CT0 from Firefox
or Chrome cookie stores. The .env config file already supports
these values, but they were only loaded into the Python config
dict — never exported to the environment of Node subprocesses.
- Add AUTH_TOKEN/CT0 to env.py config key loading
- Add set_credentials()/\_subprocess_env() to bird_x.py to inject
credentials into the env dict passed to subprocess.run/Popen
- Call set_credentials() in main() before Bird auth detection
---------
Co-authored-by: Justin Williams <jblwilliams@gmail.com>
Reorder v2.5 features: Polymarket prediction markets and HN lead as #1,
multi-signal quality-ranked relevance scoring as #2. Add Anthropic Odds
example showcasing 11 live markets from a two-word query. Add Anthropic
and OpenAI Polymarket transcripts to launch tweets.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Search Polymarket's free Gamma API for relevant prediction markets on any
topic. Uses smart multi-query expansion to cast a wider net (e.g., "Arizona
Basketball" also searches "Arizona"), merges and dedupes by event ID, and
shows price movement context ("up 22.5% this week"). No API key required.
Also hides sources with zero results from the stats output (all sources).
54 new tests, all passing. Full pipeline integration with scoring, dedupe,
cross-source linking, and rendering.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Shoutout to @ARJ999 (first HN submission, PR #12), @wkbaran
(PR #26, referenced in planning), and @gbessoni for endorsing
HN as the right addition.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Reorganize the changelog to match the real story: smarter scoring,
cross-source linking, and handle resolution as one "dramatically
better results" narrative first, then HN, then handle resolution
details. Moves blinded comparison right after the results section
as proof.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add CHANGELOG.md (Keep a Changelog format) and release-notes.md
for the v2.1.0 GitHub Release. Also includes queued copy updates:
plugin.json version bump to 2.1.0, YouTube added to descriptions,
SKILL.md security/permissions section and ClawdBot metadata,
updated watchlist examples, and v2.1 launch post refinements.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Watchlist schedules are metadata only — nothing triggers runs
automatically. Updated README to be honest that cron/launchd or an
always-on bot like Open Claw is required for automated scheduling.
Local Claude Code users can still use run-one and run-all manually.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Trevin Chow