Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add imphillip/gbrain-openclaw --skill enrichgit clone --depth 1 https://github.com/imphillip/gbrain-openclawWrote 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/skills/imphillip/gbrain-openclaw/enrich)<a href="https://agentmods.dev/skills/imphillip/gbrain-openclaw/enrich"><img src="https://agentmods.dev/badge/skills/imphillip/gbrain-openclaw/enrich.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00567 |
| Opus 5 | $0.00015 | $0.00283 |
| Sonnet 5 | $0.00006 | $0.00113 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
gbrain-enrich 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 8d 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.
What it actually says
Enrich Skill
Sources
| Source | Best for | Auth |
|---|---|---|
| Crustdata | LinkedIn profile data (90+ fields) | Token header (NOT Bearer) |
| Happenstance | Career history, network search | credits |
| Exa | Web search, articles, mentions | API key |
Person enrichment workflow
-
Find LinkedIn URL — check existing page frontmatter, or search:
gbrain get people/<slug>→ look forlinkedin:in frontmatter -
Hit Crustdata
GET https://api.crustdata.com/screener/person/enrich?linkedin_profile_url=<url> Authorization: Token <key>Returns: name, title, location, headline, skills, work history, education, twitter, email
-
Validate before writing:
- Connection count < 20 → likely wrong person. Store raw with flag, skip page update.
- Name mismatch (different last name) → skip.
- Obviously test/joke profiles → skip.
-
Store raw data:
gbrain call brain_raw '{"slug":"people/name","source":"crustdata","data":{...}}' -
Distill to page — Update compiled_truth with:
- Location, current title, company
- Education (one line, most recent degree)
- Career arc (condensed: "Google → Stripe → founded Acme")
- Top 3-5 skills
- Twitter handle, LinkedIn URL
-
DO NOT dump full data into the page. 50 skills, 10 full job descriptions → raw_data only.
Company enrichment workflow
- Search by company name or domain via Exa or Crustdata company search
- Store raw response
- Distill: founding year, stage, investors, headcount, what they build
- Update page State section
Batch rules
- Checkpoint every 20 items
- Exponential backoff on 429s: 10s → 20s → 40s → ... → 5min cap
- Never re-enrich already-enriched pages: check
gbrain call brain_raw '{"slug":"...", "source":"crustdata"}'first - Dry-run: show what would be enriched without making API calls
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.
- 8d ago First seen · 65 lines · 30 tokens per session scan A c202894d6b8d
gbrain-enrich is a skill published in the GitHub repository imphillip/gbrain-openclaw (11 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 567 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 2026-08-30.
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