agentmods.dev

assess

assess is a skill for Claude Code, Codex from bjcoombs/ai-native-toolkit. It costs 113 tokens per session (12,473 once invoked), scanned B, original, Apache-2.0.

An assessment of how ready a codebase is for contributions from AI coding agents, along with visual maps of code complexity and documentation structure.

In plain words
What is it for?
Use it to score repository practices, create a complexity hotspot map based on code size, complexity, and recent changes, and create a documentation map showing connected, unreachable, or stale documents.
Why use it?
It shows where an agent may struggle: unclear documentation, difficult code, weak checks, or frequently changing risky areas. The reports combine these signals into files saved in the repository.

Skill for Claude CodeCodex

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the ai-native-toolkit plugin — 15 skills, 7 commands, 8 agents shipped together

not rated 30 1mo ago B scan 113 tokens original Apache-2.0
View the source file bjcoombs/ai-native-toolkit
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/bjcoombs/ai-native-toolkit/assess
Any agent
npx skills add bjcoombs/ai-native-toolkit --skill assess
Clone the repo
git clone --depth 1 https://github.com/bjcoombs/ai-native-toolkit

Made for: Claude Code, Codex.

Or install ai-native-toolkit, the plugin that ships this one along with the rest of its 15 skills, 7 commands, 8 agents.

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 assess

README.md
[![agentmods](https://agentmods.dev/badge/skills/bjcoombs/ai-native-toolkit/assess.svg)](https://agentmods.dev/skills/bjcoombs/ai-native-toolkit/assess)
Your own site
<a href="https://agentmods.dev/skills/bjcoombs/ai-native-toolkit/assess"><img src="https://agentmods.dev/badge/skills/bjcoombs/ai-native-toolkit/assess.svg" alt="Measured on agentmods" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 12,473 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. 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 $0.00113 $0.12473
Opus 5 $0.00056 $0.06236
Sonnet 5 $0.00023 $0.02495
Haiku 4.5 $0.00011 $0.01247

Measured 4d ago against content hash a0052aa49e76, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

assess scanned grade B with 1 finding 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 4d ago.

The scan reads SKILL.md. This mod also ships 47 executable files (scripts/assess_core.py, scripts/assess_emit_workflow.py, scripts/assess_finalize.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

command -v apt >/dev/null && sudo apt install -y scc \
skills/assess/SKILL.md · 499 lines

How it starts

The opening of the file, as written. The whole thing — 499 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Readiness Assessment + Complexity Hotspot

Three artefacts in one pass against a target repo:

  1. Layered contract assessment - 0-8 score across navigability, runtime liveness, code design, linters, architecture tests, CI, coverage, review bots, and AI project management.
  2. Complexity hotspot SVG - Codecov-style treemap of the code. Size = LOC. Colour = cyclomatic complexity. Saturation = recent git churn. Vivid red = complex AND active = riskiest to change.
  3. Doc navigability SVG - a node-graph of the docs. Structure = connectivity (centre = entry, rim = unreachable, dashed ring = orphan); colour = staleness (vivid red = a frozen doc beside churning code = a lying map); size = file length. Folds navigability and the decaying-map signal into one artifact.

Both SVGs are colour-blind-safe by default (OrRd ramp, no red-green).

All land as files inside the target repo. The skill always writes them locally; after writing, ask the user whether to open a PR in the target repo with the artefacts.

The model: truth-pressure, not presence

Read this before scoring - it changes how you score. Across every layer, the real signal is never presence. It is whether a thing is under active pressure to stay true:

  • Tests keep behaviour honest (CI fails when it's wrong).
  • Retros / feedback loops keep the process honest (Layer 8 scores whether retros are carried out, not merely present).
  • Maintenance keeps docs honest (a wiki tracked against code churn).
  • Telemetry / liveness keeps relevance honest (is this code actually exercised).

So AI-readiness is the degree to which a codebase's self-descriptions are kept honest, not the degree to which scaffolding exists. Score artefacts on maintenance pressure, not existence. A stale-but-present doc scores at or below absent: missing makes the agent go look; confidently-stale makes it navigate fast to a wrong, current-looking conclusion.

The 9 layers (0-8) fall into three bands, ordered by dependency - what must hold for the next band to mean anything:

Read the full file on GitHub · 499 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 4d ago First seen · 499 lines · 113 tokens per session scan B a0052aa49e76

Subscribe to this mod's changes

assess is a skill published in the GitHub repository bjcoombs/ai-native-toolkit (30 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 113 tokens to every session and 12,473 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Analytics and metricsBuilding agentsagent-skillsagentic-aiai-agentsanthropicclaudeclaude-code
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