sem

A code-analysis tool that tracks changes by function, class, and other code units, instead of showing only changed lines.

In plain words
What is it for?
Use it to inspect one code unit, review a commit or branch, compare semantic and line-based diffs, find affected tests, and check history or ownership.
Why use it?
It helps you see what a change affects and avoid missing related code or tests when a raw Git diff is not enough.

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/tomsej/pi-ext/sem
Any agent
npx skills add tomsej/pi-ext --skill sem
Clone the repo
git clone --depth 1 https://github.com/tomsej/pi-ext

Made for: Claude Code, Codex.

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 726 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 $0.00075 $0.00726
Opus 5 $0.00037 $0.00363
Sonnet 5 $0.00015 $0.00145
Haiku 4.5 $0.00007 $0.00073

Measured 2d ago against content hash 0ef8a0f86fff, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sem 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/sem/SKILL.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

sem

Use the pi-sem tools as a semantic lens, not as a universal replacement for raw git diff.

Default decision tree

Choose the smallest useful tool first:

  1. Focused understanding of one entitysem_context

    • Best for a single function, method, class, block, or config section
    • Prefer this before reading a whole large file
  2. Blast radius / affected tests / hidden dependentssem_impact

    • Use when reasoning about what could break
    • Prefer scope=tests for test selection
    • Prefer scope=all when validating broader impact
  3. Structural inventory of a filesem_entities

    • Use before drilling into a suspicious file
    • Good for large files and mixed code/config files
  4. What changed across a commit/range/working treesem_diff

    • Use for semantic summaries, entity counts, and review overviews
    • Do not default to it when you only need exact patch details or a single entity
  5. History / ownership of an entitysem_log, sem_blame

    • Use for regressions, archaeology, and ownership questions

Review workflow

For commit / branch / PR review:

  1. Run sem_diff once for a semantic overview
  2. Pick the riskiest changed entities
  3. Run sem_impact on those entities
  4. Run sem_context on the suspicious ones you need to understand deeply
  5. Confirm final findings with raw git diff, read, or direct file inspection before citing line numbers

For snapshot / folder review:

  1. Start with sem_entities
  2. Use sem_context on the most relevant entities
  3. Use sem_impact only after you identify something suspicious

Important caveats

  • sem diff --format json is not always smaller than raw git diff
  • sem may under-cover tests, assets, generated files, or non-semantic glue code
  • Do not cite sem output alone as final evidence for line-level review comments
  • If semantic coverage looks incomplete, fall back to raw git diff, read, grep, and file inspection

Good prompts / tool choices

Read the full file on GitHub · 73 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. 2d ago First seen · 73 lines · 75 tokens per session scan A 0ef8a0f86fff

Subscribe to this mod's changes

sem is a skill published in the GitHub repository tomsej/pi-ext (69 stars, last pushed 15d ago), licensed MIT. It adds 75 tokens to every session and 726 once invoked, about $0.0004 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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