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 skills/oyi77/1ai-skills/code-researchnpx skills add oyi77/1ai-skills --skill code-researchgit clone --depth 1 https://github.com/oyi77/1ai-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/oyi77/1ai-skills/code-research)<a href="https://agentmods.dev/skills/oyi77/1ai-skills/code-research"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/code-research.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.02672 |
| Opus 5 | $0.00020 | $0.01336 |
| Sonnet 5 | $0.00008 | $0.00534 |
| Haiku 4.5 | $0.00004 | $0.00267 |
Grade A, and why
code-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 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.
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 — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Research Agent
Autonomous codebase analysis agent that produces structured understanding of unfamiliar code: architecture, data flows, dependencies, conventions, and entry points. This agent reads code systematically -- not randomly browsing files, but following a deliberate investigation protocol.
Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "I'll figure it out as I go" | A structured approach saves time and reduces errors. Follow the workflow in this skill rather than improvising. |
| "I already know this topic" | Familiarity breeds shortcuts. Use the checklist to verify you haven't missed critical steps. |
| "This doesn't apply to my situation" | The patterns here generalize across contexts. Adapt, don't skip — the underlying principles hold. |
| "One more tool will fix it" | Adding complexity rarely solves process gaps. Master the core workflow first. |
When to Use
Trigger phrases:
-
"code research"
-
"Joining a new project and need to understand the codebase"
-
"Investigating how a feature is implemented across multiple files"
-
"Tracing a data flow from input to output"
-
Joining a new project and need to understand the codebase
-
Investigating how a feature is implemented across multiple files
-
Tracing a data flow from input to output
-
Understanding dependency chains before making changes
-
Finding all callers of a function or users of a module
-
Mapping the architecture of a monolith or microservice
-
Preparing a technical design document that references existing code
When NOT to Use
- Implementing new features (use
code-agent) - Reviewing code quality (use
review-agent) - Refactoring code (use
refactor-agent) - Writing tests (use
test-agent) - Researching external documentation (use
web-research) - Analyzing market or competitors (use
market-research-agent) - Code is trivially simple (single file, obvious structure)
- You already know where everything is
- Real-time debugging (use
systematic-debugging)
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.
- 6d ago First seen · 321 lines · 40 tokens per session scan A 054178360f5e
code-research is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 2,672 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 2026-08-30.
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