claude-skills is a large collection of reusable skills, commands, plugins, and supporting resources for coding agents across engineering, business, research, compliance, and productivity work. It is used by people who want agents such as Claude Code, Codex, Gemini CLI, or Cursor to follow specialized workflows. The catalogue contains selected skills and settings from the collection.
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.
git clone --depth 1 https://github.com/alirezarezvani/claude-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/commands/alirezarezvani/claude-skills/cs-goal)<a href="https://agentmods.dev/commands/alirezarezvani/claude-skills/cs-goal"><img src="https://agentmods.dev/badge/commands/alirezarezvani/claude-skills/cs-goal/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/commands/alirezarezvani/claude-skills/cs-goal"><img src="https://agentmods.dev/badge/commands/alirezarezvani/claude-skills/cs-goal.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 | $0.00052 | $0.00292 |
| Opus 5.5 | $0.00021 | $0.00117 |
| Sonnet 5.5 | $0.00010 | $0.00058 |
| Haiku 4.5 | $0.00005 | $0.00029 |
Grade A, and why
cs-goal 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 today.
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.
What it actually says
/cs-goal — manage the session goal
The goal is one sentence for one agent. It selects the phase and the loop shape.
$ARGUMENTS
Run goal_state.py under agent-launcher/skills/agent-launcher-orchestrator/scripts/:
set "<goal>"→goal_state.py init --goal "<goal>"(orset --goalif it exists).status→goal_state.py status(prints goal, agent_name, phase, phases_done, loop).advance→goal_state.py advance(moves to the next phase).phase <name>→goal_state.py set --phase <name>(interview | stage-launch | grade-iterate | run-without-you | wrap-up | done).
Enable auto-surfacing each session with export AGENT_LAUNCHER_SESSION=1 (the
opt-in SessionStart hook). Two jobs → two goals in two ./my-agent-*/ folders.
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.
- today First seen · 22 lines · 52 tokens per session scan A a74b58e9fef8
cs-goal is a command published in the GitHub repository alirezarezvani/claude-skills (28,607 stars, last pushed yesterday), licensed MIT. It adds 52 tokens to every session and 292 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-24.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.
speckit.bug.test
Validate that a previously fixed bug is resolved and record the verification report.