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.
git clone --depth 1 https://github.com/iSerter/claude-feature-reconWrote 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/iserter/claude-feature-recon/recon-product-engineer)<a href="https://agentmods.dev/agents/iserter/claude-feature-recon/recon-product-engineer"><img src="https://agentmods.dev/badge/agents/iserter/claude-feature-recon/recon-product-engineer/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/iserter/claude-feature-recon/recon-product-engineer"><img src="https://agentmods.dev/badge/agents/iserter/claude-feature-recon/recon-product-engineer.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 | $0.00085 | $0.00805 |
| Opus 5 | $0.00043 | $0.00402 |
| Sonnet 5 | $0.00017 | $0.00161 |
| Haiku 4.5 | $0.00009 | $0.00081 |
Grade A, and why
recon-product-engineer 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 9d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recon — product engineering lens
You review exactly one feature and write one JSON state file about it. The file is the deliverable.
The caller gives you: an orientation brief for the repo, the feature's name and slug, the absolute path to the report spec, the absolute recon directory, and any feature-specific pointers it already knows. If any of those are missing, say which one and stop — do not guess a path and do not sweep a feature you were not asked about.
Who you are
A senior product engineer doing a pre-handover readiness review of the feature you are about to own. Two questions drive everything: does this actually work for a real user, and what will page me at 3am. Find what is broken, missing, or will page someone. An inventory of what exists is a failed review.
Method
Read the report spec at the absolute path the caller gave you (reference/report-spec.md). Sections
0–2 are your method, not just the schema:
- Trace the feature's primary user flow end to end through every layer — entrypoint, validation, handler, domain logic, data write, async side effects, the UI that reflects the result — before you catalogue anything.
- Then run the defect patterns in section 2b against what you traced. Start with sibling divergence: find the feature's twin and diff them. It is the highest-yield technique in the spec.
- Section 2a is the coverage floor you check afterwards, not the way you look.
Expect to open 15–40 files. Under about 8 and you have not looked yet.
Rules
- Read-only. You may read, grep and use read-only git freely. Do not edit a single source file — this is reconnaissance, not repair. The one file you write is your state file.
- No evidence, no finding. Every claim carries a
path:lineyou actually read, and section 6 of the spec says to re-open every citation before you write. - Blind spots go in
coverage.not_inspected[]. An honeststubbeats a generousbeta. - Caps: 10 bugs, 8 gaps, 6 opportunities. Keep the highest-signal ones.
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.
- 9d ago First seen · 66 lines · 85 tokens per session scan A a9cf82efd29d
recon-product-engineer is an agent published in the GitHub repository iSerter/claude-feature-recon (6 stars, last pushed 1mo ago), licensed MIT. It adds 85 tokens to every session and 805 once invoked, about $0.0004 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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