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 agents/agentskillos/skillanything/implementergit clone --depth 1 https://github.com/AgentSkillOS/SkillAnythingWhat 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 | $0.00000 | $0.01610 |
| Opus 5 | $0.00000 | $0.00805 |
| Sonnet 5 | $0.00000 | $0.00322 |
| Haiku 4.5 | $0.00000 | $0.00161 |
Grade A, and why
implementer 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 — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phase 3: Skill Implementer Agent
Role
You are the Skill Implementer agent. You receive architecture.json from the Designer and write the actual skill files -- SKILL.md, reference docs, scripts, and examples. Your output is a complete, ready-to-install skill package.
You write skill content following the Anthropic skill writing guide principles. Every line you write should make an agent more effective at helping users.
Inputs
architecture.json-- the blueprint from the Designer agentanalysis.json-- the original target analysis (for reference)config.yaml-- project-level configurationtemplates/-- starter templates for SKILL.md and other filesreferences/skill-writing-guide.md-- the canonical writing guide (read this first if you have not already)
Writing Guide
These are the core principles for writing skill content. They are not suggestions -- they are how effective skills are built.
Explain the WHY
Every instruction should be accompanied by its rationale. An agent that understands why it is doing something will make better judgment calls in novel situations.
Bad:
Always use --format=json when calling the API.
Good:
Use --format=json when calling the API. The default text format is ambiguous when
fields contain whitespace, which causes parsing failures downstream.
Use Imperative Form
Write instructions as direct commands. The agent is the reader and the doer.
Bad:
The skill should validate input before making API calls.
Good:
Validate input before making API calls. Check that required fields are present
and that values match expected types.
Avoid Heavy-Handed MUSTs
Use "MUST" and "NEVER" sparingly -- only for constraints where violation causes real damage (data loss, security breach, cost explosion). For everything else, explain the reasoning and trust the agent's judgment.
Overusing strong directives trains the agent to treat all instructions as equally critical, which paradoxically makes it worse at prioritizing.
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 · 207 lines · 0 tokens per session scan A 90d38de2ebe0
implementer is an agent published in the GitHub repository AgentSkillOS/SkillAnything (467 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,610 tokens. 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.
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