sawz/last30days-skill
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Revert to bash-first execution with echo progress display

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The agent in fork mode ignores text output instructions and jumps
straight to WebSearch. Reverted to the original "YOUR FIRST ACTION:
Run this command. EXECUTE." pattern that actually worked. Embedded
progress display as echo statements inside the bash command so they
can't be skipped. The agent was not running the Python script at all
when the first instruction was about text output.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Matt Van Horn
2026-02-06 10:18:53 -08:00
parent a6dd0a8b0e
commit df29bbb53d
1 changed files with 22 additions and 25 deletions
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SKILL.md
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@@ -8,38 +8,35 @@ allowed-tools: Bash, Read, Write, AskUserQuestion, WebSearch
# last30days: Research Any Topic from the Last 30 Days
## YOUR FIRST OUTPUT — before ANY tool calls
Extract the TOPIC from the user's query, then output this progress block. This text MUST appear to the user BEFORE you call Bash or WebSearch:
🔍 **{TOPIC}**
Deploying research agents:
🟠 Reddit — scanning subreddits for upvotes and comments...
🔵 X — reading posts for likes and reposts...
🌐 Web — searching blogs, docs, and news...
**DO NOT skip this. DO NOT jump to tool calls first. Output the text above, THEN call tools.**
## STEP 1: Run the Research Script
After outputting the progress block above, run:
**YOUR FIRST ACTION: Run this command. Do NOT describe this skill. Do NOT summarize workflows. Do NOT start with WebSearch. EXECUTE THIS BASH COMMAND FIRST.**
```bash
echo "🔍 Researching: $ARGUMENTS"
echo ""
echo "Deploying research agents:"
echo "🟠 Reddit — scanning subreddits for upvotes and comments..."
echo "🔵 X — reading posts for likes and reposts..."
echo "🌐 Web — searching blogs, docs, and news..."
echo ""
python3 ~/.claude/skills/last30days/scripts/last30days.py "$ARGUMENTS" --emit=compact 2>&1
```
## STEP 2: Parse User Intent (while script runs)
While that runs, parse the user's input for:
While the script runs, parse the user's input for:
1. **TOPIC**: What they want to learn about (e.g., "web app mockups", "Claude Code skills", "image generation")
2. **TARGET TOOL** (if specified): Where they'll use the prompts (e.g., "Nano Banana Pro", "ChatGPT", "Midjourney")
3. **QUERY TYPE**: What kind of research they want:
- **PROMPTING** - "X prompts", "prompting for X", "X best practices" → User wants to learn techniques and get copy-paste prompts
- **RECOMMENDATIONS** - "best X", "top X", "what X should I use", "recommended X" → User wants a LIST of specific things
- **NEWS** - "what's happening with X", "X news", "latest on X" → User wants current events/updates
- **GENERAL** - anything else → User wants broad understanding of the topic
1. **TOPIC**: What they want to learn about
2. **TARGET TOOL** (if specified): Where they'll use the prompts (e.g., "Nano Banana Pro", "ChatGPT")
3. **QUERY TYPE**:
- **PROMPTING** - "X prompts", "prompting for X", "X best practices"
- **RECOMMENDATIONS** - "best X", "top X", "what X should I use"
- **NEWS** - "what's happening with X", "X news", "latest on X"
- **GENERAL** - anything else
Common patterns:
- `[topic] for [tool]` → "web mockups for Nano Banana Pro" → TOOL IS SPECIFIED
- `[topic] prompts for [tool]` → "UI design prompts for Midjourney" → TOOL IS SPECIFIED
- Just `[topic]` → "iOS design mockups" → TOOL NOT SPECIFIED, that's OK
- "best [topic]" or "top [topic]" → QUERY_TYPE = RECOMMENDATIONS
- "what are the best [topic]" → QUERY_TYPE = RECOMMENDATIONS
**IMPORTANT: Do NOT ask about target tool before research.**
- If tool is specified in the query, use it