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 jhlee0409/all-for-claudecode --skill researchgit clone --depth 1 https://github.com/jhlee0409/all-for-claudecodeWrote 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/jhlee0409/all-for-claudecode/research)<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.
<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>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 | $0.00016 | $0.00869 |
| Opus 5 | $0.00008 | $0.00434 |
| Sonnet 5 | $0.00003 | $0.00174 |
| Haiku 4.5 | $0.00002 | $0.00087 |
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.
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:
- Official documentation (WebSearch/WebFetch)
- Codebase (existing patterns in the current project)
- Community (GitHub Issues, blogs)
3.5. Reconcile Findings
After parallel agents return, the orchestrator checks for conflicts between sources:
- Compare codebase agent findings (current usage patterns) against web agent findings (official docs, latest versions)
- 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}"
- 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}
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.
- 10d ago First seen · 120 lines · 16 tokens per session scan A ebc395caf3fb
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.
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