quality-check

quality-check is a skill for Claude Code from emergent-wisdom/understanding-graph. It costs 40 tokens per session (739 once invoked), scanned A, original, MIT.

Instructions for checking the structure of an Understanding Graph, including its gaps, connections, and unanswered questions.

In plain words
What is it for?
It is for investigating disconnected areas, bottlenecks, missing concepts, semantic gaps, and other graph-structure concerns.
Why use it?
It helps distinguish a real structural problem from a graph that is simply small or sparse.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the understanding-graph plugin — 10 skills, 2 MCP servers shipped together

Good fit It is for investigating disconnected areas, bottlenecks, missing concepts, semantic gaps, and…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/emergent-wisdom/understanding-graph/quality-check
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.

Any agent
npx skills add emergent-wisdom/understanding-graph --skill quality-check
Clone the repo
git clone --depth 1 https://github.com/emergent-wisdom/understanding-graph

Made for: Claude Code.

Or install understanding-graph, the plugin that ships this one along with the rest of its 10 skills, 2 MCP servers.

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 quality-check

README.md
[![agentmods](https://agentmods.dev/badge/skills/emergent-wisdom/understanding-graph/quality-check.svg)](https://agentmods.dev/skills/emergent-wisdom/understanding-graph/quality-check)
Your own site
<a href="https://agentmods.dev/skills/emergent-wisdom/understanding-graph/quality-check"><img src="https://agentmods.dev/badge/skills/emergent-wisdom/understanding-graph/quality-check.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 739 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00040 $0.00739
Opus 5 $0.00020 $0.00369
Sonnet 5 $0.00008 $0.00148
Haiku 4.5 $0.00004 $0.00074

Measured 6d ago against content hash 7d6a207d1475, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

quality-check 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/quality-check/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Quality Check

Use this skill deliberately, not on a timer. Do not interrupt useful work for scheduled maintenance, demand trigger diversity, or ask the user to repair the graph merely because a number is low.

Diagnose before changing

Choose the smallest view that answers the live question:

  • graph_analyze({ include: ["gaps", "bridges", "questions"] }) for islands, bridges, and genuinely unanswered questions;
  • graph_score() for a compact structural snapshot;
  • graph_centrality() when influence or bottlenecks matter;
  • graph_semantic_gaps() when embedding coverage exists and conceptual distance is relevant;
  • graph_skeleton() only when the overall topology is itself in question;
  • graph_thermostat() as an advisory entropy-style pulse, not a command.

Metrics describe the stored shape. They cannot establish truth, creativity, importance, completeness, or whether a node was worth creating. A sparse graph can be exactly right for a small task; a dense graph can still be confused.

Judge the finding in context

  • A disconnected region is a problem only if the work gives it a real relation to another region. Do not invent a bridge.
  • An unanswered question may remain intentionally open.
  • A contradiction is live conflict, not proof that either side is false.
  • A low supersession count is not evidence that someone failed to reconsider.
  • Trigger counts are descriptive. Never add questions, tensions, predictions, or any other type to improve a distribution.
  • Artifact-heavy structure is an advisory signal only. Add cognitive testimony only when genuine understanding, uncertainty, evidence, or choice exists.

When a finding could materially affect the task, use graph_suggest_next({ task, workflow }) for concrete weighted routes or graph_discover_grounded() for a bounded distant comparison. Choose, modify, combine, or reject the result. “No defensible connection” and “no repair needed” are valid outcomes.

Repair only what is real

If the diagnosis identifies a genuine issue, make the smallest truthful change:

Read the full file on GitHub · 74 lines

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 · 74 lines · 40 tokens per session scan A 7d6a207d1475

Subscribe to this mod's changes

quality-check is a skill published in the GitHub repository emergent-wisdom/understanding-graph (1 stars, last pushed 12d ago), licensed MIT. It adds 40 tokens to every session and 739 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 2026-08-31.

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