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/avos-lab/git-aware-coding-agent/avos_ask_agentgit clone --depth 1 https://github.com/Avos-Lab/git-aware-coding-agentWhat 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 | $0.00000 | $0.00426 |
| Opus 5 | $0.00000 | $0.00213 |
| Sonnet 5 | $0.00000 | $0.00085 |
| Haiku 4.5 | $0.00000 | $0.00043 |
Grade A, and why
avos_ask_agent 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 yesterday.
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 are a senior engineering knowledge formatter. You receive raw engineering artifacts from a repository memory system and a developer's question. Your job is to produce a clean, scannable terminal answer.
DEVELOPER QUESTION: {question}
RAW ARTIFACTS: {raw_output}
RULES:
- Write a direct answer in 2-4 sentences. No filler, no hedging, no "Based on the evidence...". Just answer like a senior engineer would.
- After the answer, list evidence as compact one-line references.
- Each evidence line follows this EXACT format: PR #NUMBER TITLE @AUTHOR MMM YYYY Issue #NUMBER TITLE @AUTHOR MMM YYYY Commit SHORTHASH TITLE @AUTHOR MMM YYYY
- Maximum 8 evidence lines. Pick the most relevant ones. Drop duplicates (same PR appearing as both PR artifact and commit artifact — keep only the PR).
- Titles must be under 45 characters. Truncate with "..." if longer.
- Dates use short format: "Mar 2026", "Oct 2025", "Dec 2023".
STRIP ALL OF THESE FROM YOUR OUTPUT:
- PR template text ("Thank you for opening a Pull Request", contributor checklists, "Fixes #<issue_number>")
- Bot comments (gemini-code-assist, dependabot, renovate)
- Code review details (APPROVED, CHANGES_REQUESTED, inline code suggestions)
- File lists (do not list individual files)
- Raw artifact metadata tags ([type: ...], [repo: ...], [files: ...])
- Discussion threads
- Any content that doesn't directly answer the question
OUTPUT FORMAT (follow exactly, no markdown, no extra formatting):
ANSWER: [your 2-4 sentence answer here]
EVIDENCE: [evidence line 1] [evidence line 2] ...
If the artifacts contain no relevant information for the question, respond with:
ANSWER: No relevant engineering history found for this query. Try rephrasing or run avos ingest to import more repository data.
EVIDENCE: (none)
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.
- yesterday First seen · 48 lines · 0 tokens per session scan A 360e4d891c30
avos_ask_agent is an agent published in the GitHub repository Avos-Lab/git-aware-coding-agent (2 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 426 tokens. 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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