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 PyModel/pythinker-cli --skill implement-specsgit clone --depth 1 https://github.com/PyModel/pythinker-cliWrote 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/pymodel/pythinker-cli/implement-specs)<a href="https://agentmods.dev/skills/pymodel/pythinker-cli/implement-specs"><img src="https://agentmods.dev/badge/skills/pymodel/pythinker-cli/implement-specs/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/pymodel/pythinker-cli/implement-specs"><img src="https://agentmods.dev/badge/skills/pymodel/pythinker-cli/implement-specs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00020 | $0.00207 |
| Opus 5.5 | $0.00008 | $0.00083 |
| Sonnet 5.5 | $0.00004 | $0.00041 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
implement-specs 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 1mo 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.
What it actually says
Implement Specs
Use when the task is to implement existing spec files, issue plans, or acceptance criteria.
Workflow
- Locate and read the requested spec files.
- Extract required behavior, constraints, non-goals, and verification gates.
- Scout the existing code and tests before editing.
- Produce a concise plan tied to spec requirements.
- Implement the smallest viable change.
- Run focused tests or checks.
- Compare final behavior against the spec.
Rules
- Keep changes tied directly to spec requirements.
- Ask or stop if specs conflict or are underspecified in a way that changes architecture.
- Preserve public compatibility unless the spec explicitly changes it.
- Add tests when behavior changes and a matching test layer exists.
Output
SUMMARY
IMPLEMENTED REQUIREMENTS
CHANGES
VERIFICATION
SPEC GAPS OR FOLLOW-UPS
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.
- 1mo ago First seen · 36 lines · 20 tokens per session scan A fba2c9f0284d
implement-specs is a skill published in the GitHub repository PyModel/pythinker-cli (21 stars, last pushed 3d ago), licensed Apache-2.0. It adds 20 tokens to every session and 207 once invoked, about $0.0001 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 2026-08-30.
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