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 skills/samuelzxu/claude-evolve/evolve-interviewnpx skills add samuelzxu/claude-evolve --skill evolve-interviewgit clone --depth 1 https://github.com/samuelzxu/claude-evolveWrote 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/samuelzxu/claude-evolve/evolve-interview)<a href="https://agentmods.dev/skills/samuelzxu/claude-evolve/evolve-interview"><img src="https://agentmods.dev/badge/skills/samuelzxu/claude-evolve/evolve-interview.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.04487 |
| Opus 5 | $0.00015 | $0.02243 |
| Sonnet 5 | $0.00006 | $0.00897 |
| Haiku 4.5 | $0.00003 | $0.00449 |
Grade A, and why
evolve-interview 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 3d 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 — 432 lines — stays where its author put it; the contents beside it link to each section on GitHub.
claude-evolve Interview
Ouroboros-inspired Socratic interview that refuses to start an expensive evolution run until the task specification is mathematically clear. Asks targeted questions across four dimensions, scores ambiguity after every answer, and only crystallizes into concrete artifacts (initial.py, evaluate.py, config.json) once ambiguity drops below 20%.
When this skill is invoked, immediately execute the workflow below. Do not only restate or summarize these instructions back to the user.
Purpose
Evolutionary code discovery is expensive. Each generation burns real LLM calls and wall-clock time. If the fitness function is ambiguous, the wrong code region is marked mutable, or the evaluator is unreliable, the entire run produces garbage. This skill prevents that by forcing specification clarity before execution.
Analogous to oh-my-claudecode's deep-interview, but specialized for the four dimensions that actually matter for evolution:
- Goal Clarity — What are we optimizing?
- Program Clarity — Which code is mutable?
- Evaluation Clarity — How is fitness measured (without LLM-as-judge)?
- Constraint Clarity — What must be preserved? What's the budget?
Use When
- User wants to evolve code but hasn't defined
initial.py/evaluate.pyyet - User has a vague optimization goal ("make this faster", "improve accuracy")
- User has code but isn't sure what to mark as mutable with EVOLVE-BLOCK markers
- User says "help me set up an evolution run", "interview me", "I want to evolve X"
Do Not Use When
- User already has
initial.pywith EVOLVE-BLOCK markers AND a workingevaluate.py→ run/evolvedirectly - User just wants to check status of a running evolution → run
/evolve-status - User wants to install the plugin → run
/evolve-install
Execution Policy
- Ask ONE question at a time — never batch
- Target the weakest clarity dimension with each question
- State, in one sentence before the question, why that dimension is the bottleneck
- Gather codebase facts via the
Exploresubagent BEFORE asking the user about them - For brownfield tasks, cite repo evidence (file path, function, line) in questions
- Score ambiguity after every answer and display it transparently
- Do NOT proceed to crystallization until ambiguity ≤ 0.20 (or the user explicitly exits early with a warning)
- Persist interview state for resume across interruptions
- Challenge agent modes activate at specific round thresholds to break fixation
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.
- 3d ago First seen · 432 lines · 31 tokens per session scan A 3e0454d9d45e
evolve-interview is a skill published in the GitHub repository samuelzxu/claude-evolve (16 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 4,487 once invoked, about $0.0002 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 2026-09-01.
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