how-to-research

how-to-research is a skill for Claude Code, Codex from ApexIQ/skillsmith. It costs 24 tokens per session (415 once invoked), scanned A, original, MIT.

A guide to investigating an unfamiliar codebase or technical topic instead of guessing. It covers mapping files, tracing how code runs, searching for usage, checking trusted sources, and comparing findings.

In plain words
What is it for?
Use it to understand a new project or library, find where code is used, investigate errors, research external solutions, and record verified findings.
Why use it?
It reduces the chance of making changes based on incomplete or outdated assumptions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to understand a new project or library, find where code is used, investigate errors, research external solutions, and record verified findings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/apexiq/skillsmith/how_to_research
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.

Any agent
npx skills add ApexIQ/skillsmith --skill how_to_research
Clone the repo
git clone --depth 1 https://github.com/ApexIQ/skillsmith

Made for: Claude Code, Codex.

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 how-to-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/apexiq/skillsmith/how_to_research/github.svg)](https://agentmods.dev/skills/apexiq/skillsmith/how_to_research)
Your own site
<a href="https://agentmods.dev/skills/apexiq/skillsmith/how_to_research"><img src="https://agentmods.dev/badge/skills/apexiq/skillsmith/how_to_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.

agentmods 80×15 button for how-to-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/apexiq/skillsmith/how_to_research"><img src="https://agentmods.dev/badge/skills/apexiq/skillsmith/how_to_research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 415 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00024 $0.00415
Opus 5 $0.00012 $0.00208
Sonnet 5 $0.00005 $0.00083
Haiku 4.5 $0.00002 $0.00042

Measured 10d ago against content hash 71c49efd6abc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

how-to-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 10d 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.

.agent/skills/how_to_research/SKILL.md · 50 lines

What it actually says

🔍 How to Research

Rule: Don't guess. Verify.

1. Internal Research (Codebase)

  • Map the Territory:
    • List directory structure to understand organization.
    • Read README.md, package.json, or requirements.txt first.
  • Search Smart:
    • Use grep/ripgrep to find usage of functions/classes.
    • Search for configuration files.
  • Trace the Flow:
    • Start at the entry point (main.py, index.tsx, app.ts).
    • Follow imports to understand dependencies.

2. External Research (Web)

  • Query Engineering:
    • ✅ "FastAPI rate limiting middleware best practices 2024"
    • ❌ "FastAPI slow"
  • Trusted Sources:
    • Official documentation (React, FastAPI, etc.).
    • GitHub Issues (for bug workarounds).
    • Engineering Blogs (Uber, Netflix, Stripe for architecture).
    • Stack Overflow (verify answers are up-to-date).

3. Synthesis

  • Adapt, don't copy-paste. Findings must fit your project context.
  • Cite Sources: Note where you found solutions in code comments.
  • Cross-reference: Verify information from multiple sources.

Examples

  • Understanding a new library: Official docs -> GitHub examples -> Blog tutorials.
  • Debugging an error: Error message in quotes -> Search GitHub Issues -> Stack Overflow.

Guidelines

  • Spend 5-10 mins researching before asking for help.
  • Document findings for future reference.
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. 10d ago First seen · 50 lines · 24 tokens per session scan A 71c49efd6abc

Subscribe to this mod's changes

how-to-research is a skill published in the GitHub repository ApexIQ/skillsmith (5 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 415 once invoked, about $0.0001 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.