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 commands/knowledgexlab/skill-git/revertgit clone --depth 1 https://github.com/KnowledgeXLab/skill-gitWhat 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 | $0.00080 | $0.02504 |
| Opus 5 | $0.00040 | $0.01252 |
| Sonnet 5 | $0.00016 | $0.00501 |
| Haiku 4.5 | $0.00008 | $0.00250 |
Grade A, and why
skill-git:revert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are running /skill-git:revert. Follow these steps exactly.
Task Tracking
You MUST create a task for each item below and update each task's status as you progress (pending → in_progress → completed):
- Select skill(s) — parse arguments or list registered skills for the user to choose
- Determine target version — detect dirty/clean state, resolve target tag for each skill
- Analyze changes — summarize what will be undone in plain language
- Confirm with user — show warning prompt and wait for explicit confirmation
- Execute revert — backup, reset, delete tags, update config.json
- Report result — display success/failure for each skill
Prelude
!bash "${CLAUDE_PLUGIN_ROOT}/scripts/sg-prelude.sh" $ARGUMENTS
If STATUS is not ok:
- Re-examine RAW_ARGUMENTS — check if the user expressed an agent name or intent that can be semantically resolved (e.g. a typo, a paraphrase, or an implicit default).
- If you can determine intent, note the resolution (e.g. "Treating
-a cluadeasclaude") and proceed. - If STATUS is
not_initializedand INITIALIZED_AGENTS is non-empty, suggest the user run/skill-git:init -a <agent>, or mention which agents are already available. - If STATUS is
error, display REASON as a plain-language error and stop. - If intent cannot be resolved, display a clear error and stop.
Use AGENT, GLOBAL_BASE, and SKILLS_JSON from prelude output for all subsequent steps. The skills map referred to throughout this document is the parsed content of SKILLS_JSON.
Agent name in positional position: If $ARGUMENTS contains a known agent name (claude, gemini, codex, openclaw) as a standalone positional token not preceded by -a, silently treat it as -a <agent>: override AGENT, re-read GLOBAL_BASE and SKILLS_JSON from ~/.skill-git/config.json for that agent. Do not pass it to any skill-name parsing steps.
Step 1 — Select Skill(s)
Parse $ARGUMENTS for any skill name(s) or version hints expressed in natural language. Accepted forms:
- No argument → list all registered skills and ask the user which one(s) to revert
- One or more skill names → proceed with those skills
- A version tag (e.g.
v1.0.1) → use as the target version (resolve skill interactively if ambiguous)
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.
- 2d ago First seen · 271 lines · 0 tokens per session scan A 25ecbc7cbb5f
skill-git:revert is a command published in the GitHub repository KnowledgeXLab/skill-git (41 stars, last pushed 4mo ago), licensed MIT. It adds 80 tokens to every session and 2,504 once invoked, about $0.0004 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.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.