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/aminry/auto-claude-plugins/evolve-specgit clone --depth 1 https://github.com/aminry/auto-claude-pluginsWhat 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 | $0.00015 | $0.02003 |
| Opus 5 | $0.00008 | $0.01001 |
| Sonnet 5 | $0.00003 | $0.00401 |
| Haiku 4.5 | $0.00002 | $0.00200 |
Grade A, and why
evolve-spec 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze the latest auto-develop results to discover new capabilities that are now possible or valuable, then update the capability specification accordingly.
The auto-develop skill to analyze: $ARGUMENTS
Overview
After running an auto-develop cycle, the capability specification may have room to grow — new capabilities that are now possible because of what was built, natural follow-ons, or capabilities discovered during implementation. This skill:
- Reads the latest auto-develop results and the current spec
- Analyzes what was built and what new possibilities emerged
- Identifies new capabilities that are now valuable or feasible
- Proposes additions and gets user approval
- Updates the capability spec
- Validates the updated spec consistency
Phase 1: Load Context
-
Identify the feature: Parse
$ARGUMENTSto determine the auto-develop skill name. Expected format: a feature name likesearch,auth,export, etc. -
Load the current spec: Read
.claude/commands/spec-{feature}.md(or the appropriate spec file — check.claude/commands/for the matching spec). -
Load the results log: Read
.debug/auto-develop-{feature}/results.tsvto understand the implementation trajectory — what was attempted, accepted, rejected, and in what order. -
Load the regression suite: Read
.debug/auto-develop-{feature}/regression.jsonto see all currently-tracked capabilities and baseline checks. -
Load implementation logs: Read the latest iteration's plan and verification files from
.debug/auto-develop-{feature}/logs/and.debug/auto-develop-{feature}/snapshots/to understand what was actually built and any issues encountered. -
Load the current code: Read the files that were modified during auto-develop (from git log or the implementation plans) to see the current state of the feature.
If any of these files don't exist, report what's missing and stop.
Phase 2: Analyze What Was Built
For each implemented capability ([x] status), examine:
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 · 227 lines · 15 tokens per session scan A f8c4529249ba
evolve-spec is a command published in the GitHub repository aminry/auto-claude-plugins (1 stars, last pushed 3mo ago), licensed MIT. It adds 15 tokens to every session and 2,003 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
prompt
System instructions for writing effective prompts. Apply when generating commands, skills, agents, or any LLM instructions.
audit-project-agents
This file contains detailed agent coordination for /audit-project.
audit-project
Multi-agent code review with iterative improvement.
new-sdk-app
Create and setup a new Claude Agent SDK application.
extract
Analyze conversation history and extract reusable skills, commands, or agents.
feature-new
Design and implement a new feature with parallel best-practice research, codebase exploration, architectural planning, atomic phase specs, phase-by-phase code review, and automated documentation.