Signal from Expert
SkillDocs & knowledgeLets your agent compare your notes against an expert's published ideas and return exact quotes plus gaps.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Signal from Expert skill
About this skill
Compare the user''s notes with an expert''s work on a topic. Return relevant exact quotes, source locations, and at least one gap in the user''s thinking. Use only when /signal-from-expert is explicitly invoked.
What this skill tells your AI
The instructions your AI receives, as published by davidondrej/skills in skills/thinking-and-docs/signal-from-expert/SKILL.md and read by ahel’s review.
Inputs
Require a corpus (files or folders of the user's thinking), expert, and topic. URLs are optional. Ask for missing inputs in one plain-text question.
Workflow
1. Read the corpus
Read every named file in full with cat -n. Do not read other files for context.
2. Choose sources
Check <repo>/essays/<expert-slug>/ for saved pieces. Load the deepapi skill; if the key is unset, load the DeepAPI credential using your configured method. Make 5+ separate POST /v1/search/web calls, varying <expert> <topic> queries across essays, talks, interviews, and specific sub-questions. Pick the 5–8 most relevant pieces and merge with the user's URLs and saved sources.
Show titles and URLs, one per line, and ask "go?". Wait for approval before scraping.
3. Scrape and save
From the skill directory, fetch all URLs in one batch:
python3 scripts/fetch-sources.py --expert "Paul Graham" --out <repo>/essays/paul-graham \
https://paulgraham.com/startupideas.html https://paulgraham.com/schlep.html
The helper saves each page as NN-slug.md with a header and verbatim text. Check every head/tail preview for the real first and last lines. Remove leftover layout junk without changing the prose.
If <repo>/essays/AGENTS.md is missing, copy assets/essays-AGENTS.md there.
4. Read all sources
Read every saved source in full with cat -n before writing; use its line numbers for citations.
5. Write the analysis
Use this format with 4 numbered items by default. Repeat the item block as needed, then end with the concluding paragraph:
# DD-MM-YYYY — Signal from <Expert>
Corpus: <files>. Sources: `essays/<expert-slug>/` (N pieces). Agent analysis, not the user's words.
## 1. <Short claim; prefix with "Gap:" for a gap>
<Quote the user's relevant words and explain the connection in 1–2 lines.>
> "<Exact expert quote, 1–4 sentences>"
Full section: `essays/<expert-slug>/NN-slug.md:START-END`
**Co-founder read:** <One paragraph connecting the findings and what to do next.>
- Include at least one Gap: item showing where the expert's work challenges the user's thinking or reveals something missing, backed by a quote.
- Quote both people exactly; never paraphrase the user's reasoning. Keep expert quotes short and point to full passages in saved files.
- One claim per item. Plain English. No hedging. Exclude private personal matters unrelated to the topic.
6. Save and show
Save as <corpus folder>/signal-<expert-slug>.md (a single file's parent folder). Show the full analysis in chat. Do not commit.
Failures
- Truncated source: rerun with a higher
--max-chars. - Poor search results: ask for URLs instead of guessing.
- Fewer than 3 sources: say so and ask; do not pad with weak pieces.
Signals
- GitHub stars
- 4k
- Forks
- 598
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
signal-from-expert- Source
- github.com/davidondrej/skills