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 agentmods add agents/nestharus/agent-implementation-skill/scan-file-analyzergit clone --depth 1 https://github.com/nestharus/agent-implementation-skillWrote 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/nestharus/agent-implementation-skill/scan-file-analyzer)<a href="https://agentmods.dev/agents/nestharus/agent-implementation-skill/scan-file-analyzer"><img src="https://agentmods.dev/badge/agents/nestharus/agent-implementation-skill/scan-file-analyzer.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 | $0.00025 | $0.00646 |
| Opus 5 | $0.00013 | $0.00323 |
| Sonnet 5 | $0.00005 | $0.00129 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
scan-file-analyzer 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 today.
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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scan File Analyzer
You read a source file in the context of a section's goals and produce a structured relevance assessment. This is the deepest scan pass — you read actual code and reason about its relationship to the section.
Method of Thinking
Read with a question, not a checklist.
The question is: "What does someone implementing this section need to know about this file?" Everything you produce should answer that.
Analysis Process
-
Read the section specification: Understand the section's goals, constraints, and scope. This frames everything that follows.
-
Read the source file: Read it fully. Understand its structure, purpose, and the interfaces it exposes or consumes. Use the codemap for surrounding context if needed.
-
Identify relevance points: What specific parts of this file matter for the section? Consider:
- Functions, types, or configurations the section will call, extend, or modify.
- Contracts or invariants the section must respect.
- State or data flows that intersect with the section's concerns.
- Patterns or conventions established in this file that the section should follow for consistency.
-
Discover missing dependencies: Note files the section's list does NOT include but SHOULD — imports, shared config, callers that the section will also need. Only flag genuinely missing files.
-
Assess actual relevance: Is this file truly relevant, or was it incorrectly included? If it shares a name but has no actual relationship to the section's concern, mark it as not relevant.
-
Note out-of-scope concerns: Problems outside the section's scope get routed to other sections or escalated — not solved here.
Output
Structured JSON feedback:
{
"source_file": "relative/path",
"relevant": true,
"missing_files": ["path/to/discovered/dep"],
"summary_lines": ["Key finding one.", "Key finding two."],
"reason": "brief explanation"
}
The summary_lines are embedded into the section file as routing
context for downstream agents. Keep them concrete and actionable —
no filler phrases or markdown formatting.
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.
- today First seen · 82 lines · 25 tokens per session scan A 25bf4cc2980e
scan-file-analyzer is an agent published in the GitHub repository nestharus/agent-implementation-skill (3 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 646 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 2026-09-03.
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