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 davidtoby/agent-skills --skill agent-skill-lifecyclegit clone --depth 1 https://github.com/davidtoby/agent-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/skills/davidtoby/agent-skills/agent-skill-lifecycle)<a href="https://agentmods.dev/skills/davidtoby/agent-skills/agent-skill-lifecycle"><img src="https://agentmods.dev/badge/skills/davidtoby/agent-skills/agent-skill-lifecycle/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/davidtoby/agent-skills/agent-skill-lifecycle"><img src="https://agentmods.dev/badge/skills/davidtoby/agent-skills/agent-skill-lifecycle.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 | $0.00077 | $0.00548 |
| Opus 5 | $0.00039 | $0.00274 |
| Sonnet 5 | $0.00015 | $0.00110 |
| Haiku 4.5 | $0.00008 | $0.00055 |
Grade A, and why
agent-skill-lifecycle 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 6d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Skill Lifecycle
Use this umbrella for skill collection maintenance and agent learning workflows.
Core workflow
- Determine whether the user needs discovery, authoring, publishing, migration/consolidation, or retrospective learning.
- Search existing skills before creating new ones; prefer class-level umbrella skills with references/templates/scripts over one-session micro-skills.
- When authoring, keep frontmatter concise and trigger-rich; keep SKILL.md procedural; move detailed examples into references.
- Validate structure and names before publishing or packaging.
- When mining logs, extract durable reusable procedures, not task progress.
- For proactive/self-improving systems, define explicit triggers, buffers, review cadence, and safety limits.
Labeled playbooks
Skill discovery and installation
Use search terms based on task class and domain synonyms. Prefer broad skills that cover the workflow family.
Skill creation
Follow progressive disclosure: SKILL.md for core workflow; references/ for long domain notes; templates/ for starter files; scripts/ for deterministic helpers.
Repository publishing
Update source skill, rebuild package artifacts, refresh README/package lists, and handle stale package conflicts with explicit git status checks.
Session-log recall
Use logs to recover previous decisions, commands, and errors. Condense stable lessons into skills/memory only when they are reusable.
Ontology and structured memory
Use typed entities and links when long-running projects need queryable structure beyond plain text memory.
Proactive agent patterns
Use working buffers, WAL/progress logs, autonomous cron boundaries, and user-visible summaries to avoid hidden runaway behavior.
Tool pitfalls
skill_manage.patch escape-drift on quoted text
If skill_manage(action='patch') returns Escape-drift detected, the old_string/new_string likely contains JSON-escaped quote artifacts such as \" that do not exist in the file. Do not work around by broadening the patch blindly. Re-read or inspect the target text, then retry with literal quote characters (") in the Python/JSON string value rather than backslash-prefixed quote text in the matched content.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/from-openclaw-imports-find-skills.md 5.1 KB
- references/from-openclaw-imports-ontology.md 40 KB
- references/from-openclaw-imports-proactive-agent.md 82 KB
- references/from-openclaw-imports-self-improving-agent.md 55 KB
- references/from-openclaw-imports-session-logs.md 3.9 KB
- references/from-openclaw-imports-skill-creator.md 49 KB
- references/from-user-imports-agent-skills-repo-publishing.md 4.7 KB
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.
- 6d ago First seen · 54 lines · 77 tokens per session scan A c34672c9eb67
agent-skill-lifecycle is a skill published in the GitHub repository davidtoby/agent-skills (10 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 548 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 2026-09-03.
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