guild-learn-diff

A code-change analyser that shows which parts of a project are affected by a change between two Git commits. It also lists changed files that cannot be linked to a known part of the project.

In plain words
What is it for?
Use it to assess the scope of a planned change and check whether every changed file is accounted for before verifying the work.
Why use it?
It helps reveal the likely impact of a change without relying on a raw list of changed lines. It requires an existing project knowledge graph to make those links.

Skill for Claude CodeCodex

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/lookatitude/guild/learn-diff
Any agent
npx skills add lookatitude/guild --skill learn-diff
Clone the repo
git clone --depth 1 https://github.com/lookatitude/guild

Made for: Claude Code, Codex.

Per session 175 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,743 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 $0.00175 $0.01743
Opus 5 $0.00088 $0.00872
Sonnet 5 $0.00035 $0.00349
Haiku 4.5 $0.00017 $0.00174

Measured 2d ago against content hash 15bc1f7acd42, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

guild-learn-diff 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.

skills/knowledge/learn-diff/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When to use it

Use to produce the DiffUnderstanding artifact — a graph-grounded analysis of what a base→head change set affects. It maps each changed file onto the KnowledgeGraph nodes/layers it touches and surfaces untraced_files (changed files no node explains). It is consumed at P2 by guild:plan (plan-impact) and re-read at P3 by guild:verify-done (scope-check). Part of the lazy, gated deep tier — it requires a built graph.

When not to use it

Not for the cheap-scan map (guild:learn-map), building the graph (guild:learn-graph), narrating the tour (guild:learn-onboard), or explaining a single file/module (guild:learn-explain). Not for a bare git diff with no graph grounding — the value here is mapping the diff onto graph nodes/layers, not printing hunks.

Required inputs

  • .guild/indexes/knowledge-graph.json (guild.knowledge_graph.v1) from guild:learn-graph. If absent, escalate — DiffUnderstanding is graph-grounded and cannot be synthesised from raw files.
  • A base commit (merge-base with the integration branch) and optional head.
  • The active run-id (from .guild/runs/current-run-id).
  • Frozen contract: guild.diff_understanding.v1 (schema canonical in scripts/learn/lib/schema.ts; do not re-spell field names or version strings). Output-locations table is owned by guild:learn-map.

Output format

  • .guild/runs/<run-id>/diff-learn.jsonguild.diff_understanding.v1: the changed-file set, the affected_layers / affected nodes per file, and untraced_files (changed files no graph node explains). Field names / version are canonical and frozen — conform by pointer, never copy the schema here.

Workflow steps

  1. Assert the knowledge graph exists and is readable; escalate if not.
  2. Run diff-learn.ts --cwd <root> --base <sha> [--head <sha>] [--run-id <id>] (under plugin/scripts/learn/) → the deterministic diff→node mapping.
  3. LLM half (bounded, trust the script — do not re-read source): confirm the affected_layers reading and characterise the blast radius for the plan; flag untraced_files prominently — they are the scope-creep signal P3 acts on.
  4. Write .guild/runs/<run-id>/diff-learn.json. Surface the path; do not consume it here — guild:plan (P2) and guild:verify-done (P3) own their consumption.

Read the full file on GitHub · 126 lines

Files

What ships with it

1 file 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. 2d ago First seen · 126 lines · 175 tokens per session scan A 15bc1f7acd42

Subscribe to this mod's changes

guild-learn-diff is a skill published in the GitHub repository lookatitude/guild (7 stars, last pushed 2d ago), licensed MIT. It adds 175 tokens to every session and 1,743 once invoked, about $0.0009 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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