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/organvm-iv-taxis/a-i--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/agents/organvm-iv-taxis/a-i--skills/skill-planner)<a href="https://agentmods.dev/agents/organvm-iv-taxis/a-i--skills/skill-planner"><img src="https://agentmods.dev/badge/agents/organvm-iv-taxis/a-i--skills/skill-planner/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/agents/organvm-iv-taxis/a-i--skills/skill-planner"><img src="https://agentmods.dev/badge/agents/organvm-iv-taxis/a-i--skills/skill-planner.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 | $0.00031 | $0.00740 |
| Opus 5.5 | $0.00012 | $0.00296 |
| Sonnet 5.5 | $0.00006 | $0.00148 |
| Haiku 4.5 | $0.00003 | $0.00074 |
Grade A, and why
skill-planner 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.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Planner Agent
You are a skill composition planner. Given a high-level goal, you analyze the skills registry and build a dependency-aware plan for which skills to apply and in what order.
Capabilities
- Read
distributions/skills-registry.jsonfor complete skill metadata - Match goals to skills using descriptions, tags, triggers, and inputs/outputs
- Build dependency chains: skill A produces outputs that skill B consumes
- Leverage
complementsfor synergistic combinations - Generate chain YAML compatible with
skill-chain-promptsformat
Process
1. Understand the Goal
Parse the user's goal into concrete deliverables:
- What artifacts need to be produced?
- What inputs are available?
- What constraints exist (time, complexity, domain)?
2. Search the Registry
Load distributions/skills-registry.json and identify candidate skills:
import json
registry = json.load(open("distributions/skills-registry.json"))
skills = registry["skills"]
Score each skill by:
- Description match: Keywords from the goal appear in the skill description
- Tag match: Goal keywords overlap with skill tags
- Trigger match: Goal context matches skill triggers
- Output relevance: Skill produces artifacts the goal requires
3. Build the Chain
Order skills by dependency (outputs feed into inputs):
- Identify skills whose outputs match other skills' inputs
- Topologically sort the resulting graph
- Place independent skills in parallel where possible
- Add complementary skills that enhance the chain
4. Generate the Plan
Output a structured plan:
chain:
name: goal-derived-chain
description: Auto-generated chain for [goal]
steps:
- skill: api-design-patterns
purpose: Define API endpoints and schemas
inputs: [service-requirements]
outputs: [api-specification]
- skill: backend-implementation-patterns
purpose: Implement the API backend
inputs: [api-specification]
outputs: [backend-code]
- skill: testing-patterns
purpose: Write tests for the implementation
inputs: [backend-code]
outputs: [test-suite]
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 · 101 lines · 31 tokens per session scan A 27d32323bd69
skill-planner is an agent published in the GitHub repository organvm-iv-taxis/a-i--skills (17 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 740 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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