last30days-skill/docs/plans/2026-02-06-fix-last30days-v2-formatting-reddit-citations-plan.md

title, type, date

title	type	date
fix: last30days v2 formatting, Reddit results, and citation verbosity	fix	2026-02-06

fix: last30days v2 Formatting, Reddit Results, and Citation Verbosity

Overview

Four bugs found during v2 testing across 4 queries (kanye west, howie.ai, nano banana pro prompting, open claw). The skill IS executing (the agent:Explore removal worked) but output quality has regressed from v1.

Problem Statement

#	Bug	Severity	Where
1	Stats emoji tree format ignored 3/4 times - agent renders plain text dashes instead	High	SKILL.md
2	Reddit returns 0 results for popular topics (kanye west, howie.ai)	High	scripts/lib/openai_reddit.py
3	Citations too verbose - every sentence has (per @x, @y, @z; r/sub) making summary unreadable	Medium	SKILL.md
4	Kanye summary is wall of text - no bold headers or paragraph breaks like nano banana pro got	Medium	SKILL.md

Proposed Fixes

Fix 1: Stats Emoji Format Enforcement

Root cause: The agent ignores the emoji tree template even with BAD/GOOD examples. The template uses box-drawing characters (├─ └─) that the agent treats as decorative, not mandatory.

Approach: Instead of relying on the agent to copy box-drawing characters, provide the template as a literal fill-in-the-blank with placeholders that are impossible to misinterpret.

File: SKILL.md (stats section, currently around line 190)

Change: Replace the current template + BAD/GOOD examples with a single, strict fill-in format:

Copy this EXACTLY, replacing only the {placeholders}:

---
✅ All agents reported back!
├─ 🟠 Reddit: {N} threads │ {N} upvotes │ {N} comments
├─ 🔵 X: {N} posts │ {N} likes │ {N} reposts (via Bird/xAI)
├─ 🌐 Web: {N} pages │ {domain1}, {domain2}, {domain3}
└─ 🗣️ Top voices: @{handle1} ({N} likes), @{handle2} │ r/{sub1}, r/{sub2}
---

If Reddit returned 0 threads, write: "├─ 🟠 Reddit: 0 threads (no results this cycle)"
NEVER use plain text dashes (-) or pipe (|). ALWAYS use ├─ └─ │ and the emoji.

Remove the separate BAD/GOOD section (it adds length without helping).

Fix 2: Reddit Returning 0 Results

Root cause (from code analysis):

1. openai_reddit.py:53-93 - The REDDIT_SEARCH_PROMPT instructs the OpenAI model to strip noise words before searching. For "kanye west" this isn't the issue (no noise words), but for "howie.ai" it might strip "ai".

2. openai_reddit.py:160-166 - The search is restricted to allowed_domains: ["reddit.com"] which depends on OpenAI's web_search indexing of Reddit.

3. last30days.py:474-490 - Post-retrieval filtering: normalize.filter_by_date_range() + score.score_reddit_items() + dedupe.dedupe_reddit() can discard all results if date confidence is low.

4. score.py:151-157 - Items with no engagement metrics get -10 penalty, low date confidence gets -10. Combined that's -20 which may push score below threshold.

Approach (multi-layered):

A. Add subreddit-targeted search fallback in openai_reddit.py:

• When the first search returns < 3 results, add a second search prompt that explicitly queries: "r/{topic} site:reddit.com" and "{topic} subreddit site:reddit.com"
• This catches cases where OpenAI's web_search doesn't find the obvious subreddit

B. Soften post-retrieval scoring in score.py:

• Change the no-engagement penalty from -10 to -3 (missing metrics ≠ irrelevant)
• Change low date confidence penalty from -10 to -5

C. Add minimum result guarantee in last30days.py:

• If scoring filters out ALL results, keep the top 3 by raw relevance regardless of score
• Log a warning: "All Reddit results scored below threshold, keeping top 3 by relevance"

Files to change:

• scripts/lib/openai_reddit.py - Add subreddit fallback search (lines ~160-180)
• scripts/lib/score.py - Soften penalties (lines ~151-157)
• scripts/last30days.py - Add minimum result guarantee (lines ~474-490)

Fix 3: Citations Too Verbose

Root cause: The SKILL.md instruction says "Every insight MUST cite at least one source" with a GOOD example showing (per @XXX, 15 likes; r/kanye thread with 200 upvotes) - this is too much detail per citation and the agent over-applies it.

Approach: Dial back to "cite 1-2 sources per KEY PATTERN, not per sentence. Use short format."

File: SKILL.md (citation section, currently around line 158)

Change the citation rule to:

CITATION RULE: Cite sources sparingly to prove research is real.
- In the "What I learned" intro: cite 1-2 top sources total, not every sentence
- In KEY PATTERNS: cite 1 source per pattern, short format: "per @handle" or "per r/sub"
- Do NOT include engagement metrics in citations (likes, upvotes) - save those for stats box
- Do NOT chain multiple citations: "per @x, @y, @z" is too much. Pick the strongest one.

BAD: "His album is set for March 20 (per @cocoabutterbf; Rolling Stone; HotNewHipHop; Complex)."
GOOD: "His album BULLY is set for March 20 via Gamma, per Rolling Stone."

Fix 4: Summary Formatting (Wall of Text vs Structured)

Root cause: The SKILL.md template for PROMPTING/NEWS/GENERAL shows:

What I learned:
[2-4 sentences synthesizing...]

This gives the agent permission to write a dense paragraph. The nano banana pro test got good formatting because PROMPTING queries naturally produce structured patterns. NEWS queries (kanye) produce narratives that become walls of text.

Approach: Add explicit structure to the NEWS/GENERAL format with bold topic headers.

File: SKILL.md (summary display section, around line 158)

Change the PROMPTING/NEWS/GENERAL template to:

What I learned:

**{Topic 1}** — [1-2 sentences about this storyline, per source]

**{Topic 2}** — [1-2 sentences, per source]

**{Topic 3}** — [1-2 sentences, per source]

KEY PATTERNS from the research:
1. [Pattern] — per @handle
2. [Pattern] — per r/sub
3. [Pattern] — per source

The bold topic headers force structure. Each topic gets its own paragraph with a line break. No more wall-of-text narratives.

Acceptance Criteria

• Fix 1: Stats box uses emoji tree format ├─ 🟠 🔵 🌐 └─ 🗣️ in 4/4 test queries
• Fix 2: "kanye west" returns >0 Reddit threads (r/kanye exists and is active)
• Fix 3: Summary citations are 1 per insight, short format, no engagement metrics inline
• Fix 4: NEWS/GENERAL summaries use bold topic headers with paragraph breaks, not wall of text

Test Plan

Re-run the same 4 queries after fixes:

1. /last30days kanye west — NEWS: should get Reddit results, structured summary, emoji stats
2. /last30days howie.ai — GENERAL: should get Reddit if available, citations not verbose
3. /last30days nano banana pro prompting — PROMPTING: should maintain current good quality, reduce citation density
4. /last30days open claw — GENERAL: should cite @handles in summary, emoji stats

Files to Modify

File	Fix	Change
SKILL.md	1, 3, 4	Stats template, citation rules, summary structure
scripts/lib/openai_reddit.py	2	Add subreddit fallback search
scripts/lib/score.py	2	Soften scoring penalties
scripts/last30days.py	2	Add minimum result guarantee

References

• Current SKILL.md: ~/.claude/skills/last30days/SKILL.md
• Private repo: /Users/mvanhorn/last30days-skill-private/
• Old working SKILL.md: ~/.claude/skills/last30days.backup-v1/SKILL.md
• Reddit search module: scripts/lib/openai_reddit.py:53-93 (prompt), :160-166 (API call)
• Scoring module: scripts/lib/score.py:151-157 (penalties)
• Main pipeline: scripts/last30days.py:474-490 (filtering)