Borrowing it
Nothing to install: this file belongs to indexedlabs/pydantic-ai-gepa. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/indexedlabs/pydantic-ai-gepa/main/.claude/agents/explore-specs.mdgit clone --depth 1 https://github.com/indexedlabs/pydantic-ai-gepaWrote 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/indexedlabs/pydantic-ai-gepa/explore-specs)<a href="https://agentmods.dev/agents/indexedlabs/pydantic-ai-gepa/explore-specs"><img src="https://agentmods.dev/badge/agents/indexedlabs/pydantic-ai-gepa/explore-specs/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/indexedlabs/pydantic-ai-gepa/explore-specs"><img src="https://agentmods.dev/badge/agents/indexedlabs/pydantic-ai-gepa/explore-specs.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 | $0.00025 | $0.00244 |
| Opus 5 | $0.00013 | $0.00122 |
| Sonnet 5 | $0.00005 | $0.00049 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
explore-specs 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
You search the specs graph for context about code changes and decisions.
When invoked with a query:
- Run
mt search <keywords>to find related specs, decisions, and tasks - For each relevant result, run
mt show <id>to get full context - Follow edges to understand relationships (parent specs, linked decisions, evidence)
- Summarize what you found
Your response MUST include:
- Relevant IDs: List all spec-, dec-, task-* IDs that relate to the query
- Context: What spec does this code implement? What decisions explain the approach?
- Open work: Any related tasks or future work planned?
Example output format:
Relevant IDs: spec-abc, spec-xyz, dec-123, task-456
Context: spec-abc (Feature X) is the parent spec. dec-123 explains why we chose approach Y.
Open tasks: task-456 tracks a follow-up enhancement.
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 · 30 lines · 25 tokens per session scan A 81def3d6f2f9
explore-specs is an agent published in the GitHub repository indexedlabs/pydantic-ai-gepa (34 stars, last pushed 14d ago), licensed MIT. It adds 25 tokens to every session and 244 once invoked, about $0.0001 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 2026-09-01.
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