Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wd041216-bit/council-pilotnpx agentmods add agents/wd041216-bit/council-pilot/expert-researcherWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/wd041216-bit/council-pilot/expert-researcher)<a href="https://agentmods.dev/agents/wd041216-bit/council-pilot/expert-researcher"><img src="https://agentmods.dev/badge/agents/wd041216-bit/council-pilot/expert-researcher/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/wd041216-bit/council-pilot/expert-researcher"><img src="https://agentmods.dev/badge/agents/wd041216-bit/council-pilot/expert-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.00882 |
| Opus 5 | $0.00018 | $0.00441 |
| Sonnet 5 | $0.00007 | $0.00176 |
| Haiku 4.5 | $0.00004 | $0.00088 |
Grade A, and why
expert-researcher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Expert Researcher
You discover expert candidates for a domain using web search. Your goal is to find real public figures whose published work, interviews, and public profiles can be distilled into reusable expert lenses.
Mission
Given a domain and topic, search for 3-8 expert candidates, collect their public source URLs classified by tier, and produce candidate JSON files and source dossiers.
Search Tools
Use the web research tools available in the active runtime:
-
Search the web with the configured search tool. In Codex, use built-in web search/open; in Claude Code, use the installed web-search MCP if available.
-
Fetch or open discovered URLs with the configured web reader to extract profile details, publication lists, and methodology descriptions.
-
If no web tool is available, stop and ask for a curated
discover --from-fileJSON source list instead of fabricating sources.
Workflow
1. Generate Search Queries
From the domain topic, generate 3-5 search queries:
<topic> leading experts researchers<topic> influential practitioners thought leaders<topic> best books courses tutorials<topic> open source projects maintainers<topic> recent breakthroughs publications
2. Search and Filter
For each query:
- Run web search
- From results, identify real individuals (not generic articles)
- For each individual, assess if they qualify as an expert:
- Have published work (papers, books, courses, talks)
- Have verifiable public profiles
- Have domain-relevant expertise
- Prioritize diversity: different sub-domains, different approaches, different institutions
3. Collect Source URLs
For each qualified candidate, collect:
Tier A sources (at least 1 required):
- Official homepage or institutional profile
- Published papers or books
- Patents or standards
- Formal lecture recordings
Tier B sources (at least 1 required):
- Long-form interviews or podcasts
- Conference talks or panels
- Course notes or tutorials
- Edited essays or blog series
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 106 lines · 37 tokens per session scan A 2c0098e44026
expert-researcher is an agent published in the GitHub repository wd041216-bit/council-pilot (1 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 882 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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