afc:research

afc:research is a skill for Claude Code from jhlee0409/all-for-claudecode. It costs 16 tokens per session (869 once invoked), scanned A, original, MIT.

A technical research workflow that investigates a question about software technologies, such as comparing libraries or exploring an API. It saves the conclusions in the project’s research memory for later use.

In plain words
What is it for?
Comparing libraries, planning technology choices, researching migrations, and recording technical conclusions for the project.
Why use it?
It brings together information from official documentation, the codebase, and community sources, while checking whether related research already exists. Independent investigations can cover the topic from different angles.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Part of the afc plugin — 29 skills, 12 agents, 19 hooks shipped together

Good fit Comparing libraries, planning technology choices, researching migrations, and recording technical conclusions for the project.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jhlee0409/all-for-claudecode/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 jhlee0409/all-for-claudecode --skill research
Clone the repo
git clone --depth 1 https://github.com/jhlee0409/all-for-claudecode

Made for: Claude Code.

Or install afc, the plugin that ships this one along with the rest of its 29 skills, 12 agents, 19 hooks.

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 afc:research

README.md
[![agentmods](https://agentmods.dev/badge/skills/jhlee0409/all-for-claudecode/research/github.svg)](https://agentmods.dev/skills/jhlee0409/all-for-claudecode/research)
Your own site
<a href="https://agentmods.dev/skills/jhlee0409/all-for-claudecode/research"><img src="https://agentmods.dev/badge/skills/jhlee0409/all-for-claudecode/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 afc:research

Your own site · 80×15
<a href="https://agentmods.dev/skills/jhlee0409/all-for-claudecode/research"><img src="https://agentmods.dev/badge/skills/jhlee0409/all-for-claudecode/research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 869 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 $0.00016 $0.00869
Opus 5 $0.00008 $0.00434
Sonnet 5 $0.00003 $0.00174
Haiku 4.5 $0.00002 $0.00087

Measured 10d ago against content hash ebc395caf3fb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

afc: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.

skills/research/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/afc:research — Technical Research

Investigates technical questions and summarizes conclusions. Results are persisted to .claude/afc/memory/research/{topic}.md.

Arguments

  • $ARGUMENTS — (required) research topic (e.g., "Zustand v5 migration", "WebCodecs API comparison")

Execution Steps

1. Analyze Topic

Extract from $ARGUMENTS:

  • Core question: What do we need to know?
  • Context: Why is it needed? (relevance to the current project)
  • Scope: Depth vs breadth (specific library comparison? general technology trends?)

2. Check Existing Research

Check .claude/afc/memory/research/ directory for related prior research:

  • If found: load existing content and decide whether an update is needed
  • If not found: proceed with new research

3. Gather Information

Use Agent Teams — run independent investigations in parallel:

Task("WebSearch: {topic} official docs", subagent_type: "general-purpose")
Task("Codebase: analyze current usage patterns", subagent_type: "general-purpose")

Source priority:

  1. Official documentation (WebSearch/WebFetch)
  2. Codebase (existing patterns in the current project)
  3. Community (GitHub Issues, blogs)

3.5. Reconcile Findings

After parallel agents return, the orchestrator checks for conflicts between sources:

  1. Compare codebase agent findings (current usage patterns) against web agent findings (official docs, latest versions)
  2. If a codebase pattern conflicts with official documentation (e.g., deprecated API, changed behavior in newer version):
    • Flag the conflict explicitly in Findings rather than silently adopting one source
    • Note: "Current codebase uses {pattern} but official docs recommend {alternative} since {version/date}"
  3. If no conflicts → proceed to Summarize

4. Summarize Conclusions

# Research: {topic}

> Date: {YYYY-MM-DD}
> Related feature: {related feature or "general"}

## Core Question
{what we needed to know}

## Findings

### {subtopic 1}
{content}
**Source**: {URL} (verified {date})

### {subtopic 2}
{content}

## Option Comparison (if applicable)
| Criterion | {OptionA} | {OptionB} | {OptionC} |
|-----------|-----------|-----------|-----------|
| {criterion1} | {evaluation} | {evaluation} | {evaluation} |
| {criterion2} | {evaluation} | {evaluation} | {evaluation} |

## Conclusion
**Recommendation**: {choice or conclusion}
**Rationale**: {key reason}
**Caveats**: {pitfalls or constraints}

## Project Application
{how this can be applied in the current project}

Read the full file on GitHub · 120 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. 10d ago First seen · 120 lines · 16 tokens per session scan A ebc395caf3fb

Subscribe to this mod's changes

afc:research is a skill published in the GitHub repository jhlee0409/all-for-claudecode (7 stars, last pushed 5mo ago), licensed MIT. It adds 16 tokens to every session and 869 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.