skill-hunter AGENTS.md

A set of instructions for working on Skill Hunter, a project that helps agents look for existing tools, skills, repositories, templates, and related resources before implementing something new.

In plain words
What is it for?
Use it when modifying or reviewing Skill Hunter. It covers responsibilities, tool usage, safety boundaries, acceptance checks, and final reporting.
Why use it?
It establishes rules for deciding what to search for, preserving existing behavior, and verifying requested changes.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/mturac/skill-hunter/agents-md
Clone the repo
git clone --depth 1 https://github.com/mturac/skill-hunter

Made for: Codex, OpenCode.

Per session 739 This file is loaded in full into every session.
When invoked 739 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00739 $0.00739
Opus 5 $0.00369 $0.00369
Sonnet 5 $0.00148 $0.00148
Haiku 4.5 $0.00074 $0.00074

Measured 2d ago against content hash 548bb20ab213, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

skill-hunter AGENTS.md 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 2d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

AGENTS.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file guides Codex/OpenAI agents working with Skill Hunter.

Precedence Contract

Safety > privacy > tool schema > user constraints > task style. Later examples, shortcuts, or skip rules never override higher-priority boundaries. Conflicts require a short clarification question or the safer path.

Responsibility Contract

Role: accountable engineering assistant for the current user request. Owned surface: only the requested files, module, component, workflow, or documentation. Constraints and non-goals: preserve existing install paths, runtime names, safety gates, and documented behavior. Acceptance: the requested outcome is complete and reviewable. Verification: run the smallest relevant test, audit, or syntax check available. Final report: changed files, verification results, and residual risk.

Core Rule

Avoid immediate implementation. First decide whether the request could benefit from an existing skill, MCP server, CLI tool, plugin, GitHub repository, automation template, workflow, code generator, SDK, API, browser extension, design/code asset, documentation pack, or internal project utility.

Question to answer: "Is there likely an existing skill/tool/workflow that can solve or accelerate this task?"

Search or reason about candidates, evaluate them, and present the best option before execution.

Tool Contract

No invented tool calls. Treat tools as candidates until the host exposes a callable tool with a concrete schema. Required JSON schema:

{
  "goal": "string",
  "decision": "USE_EXISTING | ADAPT_EXISTING | BUILD_MINIMAL | BUILD_CUSTOM | ASK_USER | AVOID",
  "candidates_checked": ["string"],
  "recommended_path": "string",
  "risk": "LOW | MEDIUM | HIGH | CRITICAL",
  "approval_required": true,
  "next_action": "string"
}

Low confidence or missing required context maps to ASK_USER.

Skill Discovery Pass

Trigger for file conversion, PDF/DOCX/PPTX generation, browser automation, data extraction, scraping, testing, deployment, CI/CD, image/video generation, design-to-code, API integration, code migration, documentation generation, project scaffolding, database analysis, cloud setup, LLM orchestration, and agent workflows.

Read the full file on GitHub · 78 lines

Changes

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.

  1. 2d ago First seen · 78 lines · 739 tokens per session scan A 548bb20ab213

Subscribe to this mod's changes

skill-hunter AGENTS.md is an instructions file published in the GitHub repository mturac/skill-hunter (2 stars, last pushed 3mo ago), licensed MIT. It adds 739 tokens to every session, about $0.0037 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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