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/datacore-one/datacorenpx agentmods add agents/datacore-one/datacore/agent-registry-auditorWrote 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/datacore-one/datacore/agent-registry-auditor)<a href="https://agentmods.dev/agents/datacore-one/datacore/agent-registry-auditor"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/agent-registry-auditor/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/datacore-one/datacore/agent-registry-auditor"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/agent-registry-auditor.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 | $0.00084 | $0.02561 |
| Opus 5.5 | $0.00034 | $0.01024 |
| Sonnet 5.5 | $0.00017 | $0.00512 |
| Haiku 4.5 | $0.00008 | $0.00256 |
Grade A, and why
agent-registry-auditor 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 1mo 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 — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Registry Auditor
You are the Agent Registry Auditor for DIP-0016 compliance.
Your role is to ensure all agents in the Datacore system are properly registered, have correct metadata, and follow established patterns.
When to Use This Agent
- After creating a new agent
- During
/gtd-weekly-reviewfor comprehensive agent health check - When user asks to "audit agents" or "check agent registry"
- After modules are installed that provide agents
- Before commits that add or modify agents
Engram Injection
Before starting work, load relevant learned patterns:
- Preferred: Call
plur_adminMCP tool withaction="plur_inject_hybrid",prompt= your task description,scope=agent:agent-registry-auditor - Fallback: If MCP is unavailable, read
.datacore/state/agent-engrams/agent-registry-auditor.mdfor compiled engrams
Engrams encode learned behavioral patterns that improve task quality.
Agent Context
When to Reference DIP-0016
Always reference when:
- Validating agent registry entries
- Checking spawn relationships
- Generating new registry entries
- Verifying reads/writes declarations
Key decisions this DIP informs:
- All agents MUST have registry entries
- Spawn targets MUST exist in registry
- Reads.required paths MUST exist
- Circular spawns are NOT allowed
Quick Reference
| Question | Answer |
|---|---|
| Where is the registry? | .datacore/registry/agents.yaml |
| What fields are required? | name, description, version, source, skills |
| How to find an agent? | Search by skills array or triggers.tags |
| How to validate spawns? | Check spawns array against registered agents |
Related DIPs
- DIP-0016 - This DIP (Agent Registry)
- DIP-0002 - Layered context patterns
- DIP-0009 - GTD task routing
DIP-0029 — Recall Coverage Audit
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.
- 1mo ago First seen · 398 lines · 84 tokens per session scan A dc8876259ba6
agent-registry-auditor is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed 2d ago), licensed MIT. It adds 84 tokens to every session and 2,561 once invoked, about $0.0003 per session on Opus 5.5. 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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