self-assess

self-assess is a skill for Claude Code, Codex from yologdev/yoyo-evolve. It costs 20 tokens per session (510 once invoked), scanned A, original, MIT.

A self-review process for an AI coding agent that examines its own code, past lessons, and behavior on small tasks to find problems.

In plain words
What is it for?
Use it to inspect source files, review previous mistakes, test edge cases, and identify concrete improvements.
Why use it?
It helps reveal crashes, unclear errors, missing features, and other weaknesses that ordinary task work may miss.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

About the project

yoyo-evolve is a terminal coding agent that reads and changes its own Rust source code, runs tests, and commits its improvements. It is for users who want an autonomous agent that can navigate codebases, edit multiple files, run tests, manage Git, and recover from failures. The catalogue entries are skills for working with this coding agent.

yologdev/yoyo-evolve · 1,869 stars · on GitHub · yoyo.yolog.dev

Install

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.

agentmods
npx agentmods add skills/yologdev/yoyo-evolve/self-assess
Any agent
npx skills add yologdev/yoyo-evolve --skill self-assess
Clone the repo
git clone --depth 1 https://github.com/yologdev/yoyo-evolve

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for self-assess

README.md
[![agentmods](https://agentmods.dev/badge/skills/yologdev/yoyo-evolve/self-assess.svg)](https://agentmods.dev/skills/yologdev/yoyo-evolve/self-assess)
Your own site
<a href="https://agentmods.dev/skills/yologdev/yoyo-evolve/self-assess"><img src="https://agentmods.dev/badge/skills/yologdev/yoyo-evolve/self-assess.svg" alt="Measured on agentmods" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 510 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00020 $0.00510
Opus 5 $0.00010 $0.00255
Sonnet 5 $0.00004 $0.00102
Haiku 4.5 $0.00002 $0.00051

Measured 6d ago against content hash 6c43ffd00096, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

self-assess 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 6d 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.

skills/self-assess/SKILL.md · 50 lines

What it actually says

Self-Assessment

You are assessing yourself. Your source code is your body. Read it critically.

Process

  1. Survey your source code — use list_files to map the modules, then read the entry points and the areas that matter (wc -l for sizes). src/ is large; you don't need to read every file.
  2. Read memory/active_learnings.md. Check your accumulated lessons — patterns that worked, mistakes to avoid, insights from past sessions. Build on what you already know.
  3. Try using yourself. Pick a small real task and attempt it:
    • Edit a file and check the result
    • Run a shell command that might fail
    • Try an edge case (empty input, long input, special characters)
  4. Note what went wrong. Be specific:
    • Did you crash? Where?
    • Did you give a bad error message? What should it say?
    • Was something slow or clunky?
    • Is there a feature you needed but didn't have?
  5. Check journals/JOURNAL.md. Have you tried something before that failed? Don't repeat the same mistake.

What to look for

  • unwrap() calls — these are potential panics. Every one is a bug waiting to happen.
  • Missing error messages — if something fails silently, that's a problem.
  • Hard-coded values — magic numbers, hard-coded paths, assumptions about the environment.
  • Missing edge cases — what happens with empty input? Unicode? Very long strings?
  • User experience gaps — is anything confusing, unclear, or annoying?
  • Verification gaps — tests that pass but don't actually exercise the changed behavior.

Output

Write your findings as a prioritized list. The most impactful issue goes first. Ground each finding in evidence — the file:line, command output, or test result that shows it, not a hunch or something you half-remember. Format:

SELF-ASSESSMENT Day [N]:
1. [CRITICAL/HIGH/MEDIUM/LOW] Description of issue — evidence: file:line / command / test result
2. ...

Then prioritize which ones to tackle this session. Fix as many as you can.

Changes

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.

  1. 6d ago First seen · 50 lines · 20 tokens per session scan A 6c43ffd00096

Subscribe to this mod's changes

self-assess is a skill published in the GitHub repository yologdev/yoyo-evolve (1,869 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 510 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 2026-08-30.

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