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 skills add jggomez/expert-ai-developer-skills --skill repo-researchgit clone --depth 1 https://github.com/jggomez/expert-ai-developer-skillsWrote 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/skills/jggomez/expert-ai-developer-skills/repo-research)<a href="https://agentmods.dev/skills/jggomez/expert-ai-developer-skills/repo-research"><img src="https://agentmods.dev/badge/skills/jggomez/expert-ai-developer-skills/repo-research/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/skills/jggomez/expert-ai-developer-skills/repo-research"><img src="https://agentmods.dev/badge/skills/jggomez/expert-ai-developer-skills/repo-research.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 | $0.00055 | $0.01129 |
| Opus 5.5 | $0.00022 | $0.00452 |
| Sonnet 5.5 | $0.00011 | $0.00226 |
| Haiku 4.5 | $0.00006 | $0.00113 |
Grade A, and why
repo-research 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Research Skill
Overview
This skill maps a repository's stack, directory boundaries, executable commands, and architectural invariants into a concise, high-signal Codebase Map at .agents/rules/project-context.md (<= 80 lines), while bootstrapping or synchronizing target-project root AGENTS.md (<= 90 lines) and context/memory/MEMORY.md (<= 80-100 lines). It prioritizes deterministic script extraction over speculative file reading to conserve tokens.
When to Use
Trigger Scenarios
- Onboarding onto an unfamiliar repository or refreshing
.agents/rules/project-context.md. - Bootstrapping or syncing a target repository's root
AGENTS.mdandcontext/memory/MEMORY.md. - Verifying build, lint, and test commands alongside entry points and layer invariants.
- Reconciling contradictions between stale documentation and actual source code.
When NOT to Use
- Bulk-reading entire source trees without running
repo_analyzer.pyfirst. - Deep code smell or SOLID auditing: Route to
code-smells-expertorcode-critic. - Feature-level PRD, UI design, or MADR authoring: Route to discovery skills (
docs/<feature-name>/).
Process
Phase 1: Automated Repository Extraction
Run the analyzer script to extract directory layout, languages, package managers, config files, and entry points into .agents/rules/project-context.md:
python3 ./skills/repo-research/scripts/repo_analyzer.py
Phase 2: High-Signal Codebase Map Refinement (<= 80 lines)
Inspect only high-signal config and entry files (pyproject.toml, package.json, Makefile, pubspec.yaml, main entry points) to replace [...] placeholders across the 4 core sections — keeping .agents/rules/project-context.md strictly <= 80 lines:
- Stack & Entry Points: Verified runtime versions, frameworks, data stores, and entry modules.
- Directory & Layer Map: Concise tree plus domain, interface/UI, and test directory ownership.
- Run, Build & Test Commands: Exact, verified install, dev, lint/typecheck, scoped test, and full test commands.
- Key Architectural & Env Invariants: Layer boundaries, required env vars (names only, zero secrets), and runtime constraints.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 71 lines · 55 tokens per session scan A 5dee00b82225
repo-research is a skill published in the GitHub repository jggomez/expert-ai-developer-skills (30 stars, last pushed yesterday), licensed Apache-2.0. It adds 55 tokens to every session and 1,129 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-11-06.
repo-research compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| repo-researchjggomez/expert-ai-developer-skills | Skill | 30 | yesterday | Apache-2.0 | A | 55 | Claude Code, Codex |
| knowledge-ingestopenclaw/openclaw | Skill | 394k | yesterday | MIT | A | 80 | Claude Code, Codex |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 68k | 2d ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| forgetasgeirtj/system_prompts_leaks | Skill | 71k | 2d ago | CC0-1.0 | A | 74 | Claude Code, Codex |
| Cortexdanielmiessler/LifeOS | Skill | 20k | yesterday | MIT | A | 184 | Claude Code |
| memoryopensquilla/opensquilla | Skill | 7.1k | 6d ago | Apache-2.0 | A | 44 | Claude Code, Codex |
| ha-data-storesshiwenwen/hope-agent | Skill | 1.9k | yesterday | MIT | A | 115 | Claude Code, Codex |