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 karashiiro/agent-skills --skill investigating-open-source-projectsgit clone --depth 1 https://github.com/karashiiro/agent-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/karashiiro/agent-skills/investigating-open-source-projects)<a href="https://agentmods.dev/skills/karashiiro/agent-skills/investigating-open-source-projects"><img src="https://agentmods.dev/badge/skills/karashiiro/agent-skills/investigating-open-source-projects/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/karashiiro/agent-skills/investigating-open-source-projects"><img src="https://agentmods.dev/badge/skills/karashiiro/agent-skills/investigating-open-source-projects.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 | $0.00039 | $0.01399 |
| Opus 5 | $0.00019 | $0.00700 |
| Sonnet 5 | $0.00008 | $0.00280 |
| Haiku 4.5 | $0.00004 | $0.00140 |
Grade A, and why
investigating-open-source-projects 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigating Open-Source Projects
Overview
Choose a research strategy based on the type of question. Different question types benefit from different tool combinations. GitHub's structured API tools excel at code-level and issue-level investigation; web search excels at finding blogs, release announcements, and ecosystem context.
Research Patterns
Implementation Discovery
Trigger: "How does X implement Y?" / "What patterns do libraries use for Z?"
Search for source code across repositories, then read implementations directly.
- Search code with targeted queries scoped by repo, language, and path
- Read 2-3 of the most relevant source files
- Compare patterns across implementations
-- Find implementations
local results = github.search_code({
query = 'symbol:retryWithBackoff language:typescript path:src NOT path:test'
}):await()
-- Read a file from results
local file = github.get_file_contents({
owner = "some-org", repo = "some-repo", path = "src/retry.ts"
}):await()
result({ search = results, file = file })
Best for: finding how multiple projects solve the same problem. Especially strong for obscure libraries with sparse documentation — code search finds implementations that web search cannot.
Decision Archaeology
Trigger: "Why did project X choose Y over Z?" / "What alternatives were considered?"
Reasoning lives in issue discussions, PR comments, and blog posts. Search for the discussion, not the code.
- Search issues and PRs in the project for the feature/decision
- Read key issues to find debate and rationale
- Check blog posts or release notes for additional context
-- Find relevant issues
local issues = github.search_issues({
query = 'repo:prisma/prisma "json filtering" is:issue'
}):await()
-- Read an issue with comments
local detail = github.issue_read({
owner = "prisma", repo = "prisma", issueNumber = 2444
}):await()
result({ issues = issues, detail = detail })
Best when combined with web search for blog posts and release announcements that explain the "why" in the team's own words.
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.
- 9d ago First seen · 150 lines · 39 tokens per session scan A d47ee39478f9
investigating-open-source-projects is a skill published in the GitHub repository karashiiro/agent-skills (2 stars, last pushed 4mo ago), licensed Unlicense. It adds 39 tokens to every session and 1,399 once invoked, about $0.0002 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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