github-deep-research

github-deep-research is a skill for Claude Code from HezaoHezao/poirot. It costs 18 tokens per session (1,242 once invoked), scanned C, original, MIT.

A research method for examining any GitHub repository, which is an online project codebase. It combines repository data, web searches, and browsing to build a detailed report.

In plain words
What is it for?
Use it to study a repository’s architecture, timeline, contributors, feature development, community activity, or competitive position.
Why use it?
It brings the project’s code, history, contributors, issues, and surrounding information into one investigation. This makes it easier to understand how the project is built and has changed.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

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 skills/hezaohezao/poirot/github-deep-research
Any agent
npx skills add HezaoHezao/poirot --skill github-deep-research
Clone the repo
git clone --depth 1 https://github.com/HezaoHezao/poirot

Made for: Claude Code.

Wrote 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.

agentmods badge for github-deep-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/hezaohezao/poirot/github-deep-research.svg)](https://agentmods.dev/skills/hezaohezao/poirot/github-deep-research)
Your own site
<a href="https://agentmods.dev/skills/hezaohezao/poirot/github-deep-research"><img src="https://agentmods.dev/badge/skills/hezaohezao/poirot/github-deep-research.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,242 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 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 5.1 $0.00018 $0.01242
Opus 5 $0.00009 $0.00621
Sonnet 5 $0.00004 $0.00248
Haiku 4.5 $0.00002 $0.00124

Measured 6d ago against content hash a281a58db8f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade C, and why

github-deep-research scanned grade C with 2 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 6d 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.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -s "https://api.github.com/repos/$OWNER/$REPO" | python3 -c "

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

> version uses `bash` with `curl` to the GitHub API directly + `gh` CLI when
poirot/backend/agents/skill/builtin_skills/research/github-deep-research/SKILL.md · 155 lines

How it starts

The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub Deep Research

Multi-round research combining GitHub API, web_search, and browse_page to produce comprehensive markdown reports on any GitHub repository.

Poirot note: The original deer-flow skill uses a bundled scripts/github_api.py helper. Poirot doesn't bundle that script, so this version uses bash with curl to the GitHub API directly + gh CLI when available.

When to Use

  • User provides a GitHub repository URL
  • User asks for comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of an open source project
  • User wants to understand a project's architecture, history, or community

Research Workflow

  • Round 1: GitHub API (repo metadata, README, file tree, contributors, commits)
  • Round 2: Discovery (web search for overview, competitors)
  • Round 3: Deep Investigation (architecture, timeline, community sentiment)
  • Round 4: Deep Dive (commit history, issues/PRs for feature evolution)

Round 1 — GitHub API

Setup

# Resolve owner/repo from remote URL
REMOTE_URL=$(git remote get-url origin 2>/dev/null || echo "")
# Or user provides owner/repo directly
OWNER="owner"
REPO="repo"

Repo metadata via curl

# Repo summary
curl -s "https://api.github.com/repos/$OWNER/$REPO" | python3 -c "
import sys, json
r = json.load(sys.stdin)
print(f'Name: {r[\"full_name\"]}')
print(f'Description: {r[\"description\"]}')
print(f'Stars: {r[\"stargazers_count\"]}')
print(f'Forks: {r[\"forks_count\"]}')
print(f'Language: {r[\"language\"]}')
print(f'License: {r.get(\"license\",{}).get(\"spdx_id\",\"N/A\")}')
print(f'Created: {r[\"created_at\"][:10]}')
print(f'Updated: {r[\"updated_at\"][:10]}')
"

# README
curl -s "https://api.github.com/repos/$OWNER/$REPO/readme" | python3 -c "
import sys, json, base64
r = json.load(sys.stdin)
print(base64.b64decode(r['content']).decode('utf-8'))
"

# Recent commits
curl -s "https://api.github.com/repos/$OWNER/$REPO/commits?per_page=10" | python3 -c "
import sys, json
for c in json.load(sys.stdin):
    print(f'{c[\"sha\"][:7]} {c[\"commit\"][\"author\"][\"date\"][:10]} {c[\"commit\"][\"message\"].splitlines()[0][:80]}')
"

# Languages
curl -s "https://api.github.com/repos/$OWNER/$REPO/languages"

# Contributors
curl -s "https://api.github.com/repos/$OWNER/$REPO/contributors?per_page=10" | python3 -c "
import sys, json
for c in json.load(sys.stdin):
    print(f'{c[\"login\"]:20s} {c[\"contributions\"]} commits')
"

Read the full file on GitHub · 155 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. 6d ago First seen · 155 lines · 18 tokens per session scan C a281a58db8f3

Subscribe to this mod's changes

github-deep-research is a skill published in the GitHub repository HezaoHezao/poirot (215 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,242 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

commit

Atomic git commit with conventional message. Use when the user says "commit", "save my changes", "commit this", or wants to create a git commit. Stages specific files, writes a conventional commit message with body explaining non-obvious decisions. Never uses git add -A.

congchuanling-dot/Cohort · 59 tokens

python-run

Run and debug Python scripts in the project. Use when the user says "run python", "execute this script", "debug this py file", or wants to run/modify a .py file. Handles dependency checks, linting, execution, and error analysis.

congchuanling-dot/Cohort · 56 tokens

hqe

Comprehensive codebase health auditing, remediation, and verification skill based on the canonical HQE Protocol v5.0.0.

spearchucker667/Skill-HQE · 29 tokens

cost-efficiency-analyzer

Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for "are we spending too…

awslabs/agentcore-samples · 98 tokens

computer-use

Read and drive native desktop applications through the accessibility layer — list on-screen apps, snapshot one window as a numbered element tree, then click / type / set a value / scroll / drag / run a named action, by element index or by screen coordinates. Use for work in a desktop app rather than a web page. Full…

kirodotdev/KiroCrew · 105 tokens

goal-conductor

Own a long-horizon goal end to end - decompose it into work items, stand up one top-level session per item, patrol their state on a nudge loop, and decide each next round until the goal is met or a stop condition fires. Use when the user hands over a goal too large for one session ("clear the flaky-test backlog"…

kirodotdev/KiroCrew · 105 tokens