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Agent skill

Assessing Impact

by oaustegard in oaustegard/claude-skills

Pre-change blast-radius report for a symbol or file. An agent skill from oaustegard/claude-skills.

MITAuto-check passed

Install Assessing Impact

skills CLI
$ npx skills add oaustegard/claude-skills --skill assessing-impact -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install oaustegard/claude-skills assessing-impact --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/assessing-impact .claude/skills/assessing-impact && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
assessing-impact
GitHub stars
150
Token cost
~1.4k tokens
SKILL.md length
524 words
Files
4 (incl. scripts)
Skills in repo
66
Repo updated
First seen
Licence
MIT

At a glance

Pre-change blast-radius report for a symbol or file. An agent skill from oaustegard/claude-skills.

  • Works in 3 steps: Run the report → Read the data, write the summary → Drill if needed
  • About to refactor
  • SKILL.md covers Setup, Workflow, Options and Output Sections, plus 3 more sections
  • Runs Python scripts from its folder; calls uv

What it does

Assessing Impact is an agent skill from oaustegard/claude-skills. Pre-change blast-radius report for a symbol or file. Walks tree-sitting references, augments with a plain-text scan over non-parsed files (configs, plain docs), and clusters affected sites by feature (FEATURES.md) or top-level package. Use when about to refactor, rename, or delete something in a repo you don't own — "what breaks if I change validateUser", "who calls this", "is this safe to remove", "where is this used", "blast radius", "impact analysis". This is the CONVERGENT pre-change risk skill — for "what is…

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `CHANGELOG.md`, `README.md` and `scripts/impact.py`).

The repository describes itself as: My collection of Claude skills. The licence is MIT.

When your agent uses it

  • About to refactor
  • Delete something in a repo you dont own — what breaks if I change validateUser
  • Is this safe to remove
  • Where is this used

Example prompts

  • “t own —”
  • “who calls this”
  • “is this safe to remove”
  • “/assessing-impact”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Run the report
  2. Read the data, write the summary
  3. Drill if needed

What it can do on your machine

Read from SKILL.md and the folder at commit cf49d47. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Assessing Impact loads about 1.4k tokens when it runs. Until then it costs about 155 tokens; SKILL.md has 524 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~155
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from oaustegard/claude-skills at commit cf49d47, republished under its MIT licence (© oaustegard). 524 words, ~1,367 tokens.

Download SKILL.mdSave it as .claude/skills/assessing-impact/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
assessing-impact
description
Pre-change blast-radius report for a symbol or file. Walks tree-sitting references, augments with a plain-text scan over non-parsed files (configs, plain docs), and clusters affected sites by feature (`_FEATURES.md`) or top-level package. Use when about to refactor, rename, or delete something in a repo you don't own — "what breaks if I change `validateUser`", "who calls this", "is this safe to remove", "where is this used", "blast radius", "impact analysis". This is the CONVERGENT pre-change risk skill — for "what is this repo?" use exploring-codebases; for "where is X?" use searching-codebases.
metadata.version
0.1.1

Assessing Impact

Cheap, ad-hoc impact analysis for a single target. Not a graph database — a focused walk over an AST cache plus a complementary text scan, clustered into a report that's easy to summarize.

Use this when you're about to refactor / rename / delete a symbol in a repo you don't work in daily, and you want a single artifact that says: "these N files will need to change, in these M packages, with these tests likely affected."

Don't use this for deep ongoing impact analysis on your own codebase — stand up GitNexus, SourceGraph, or your IDE's index. This skill is for the one-shot case.

Setup

bash
uv venv /home/claude/.venv 2>/dev/null
uv pip install --python /home/claude/.venv/bin/python tree-sitter
export PYTHON=/home/claude/.venv/bin/python
export IMPACT=/mnt/skills/user/assessing-impact/scripts/impact.py

The script depends on the tree-sitting skill — it imports engine.py directly. The bundled grammars live with tree-sitting; no separate language-pack install needed.

Workflow

1. Run the report
bash
$PYTHON $IMPACT /path/to/repo SYMBOL_NAME

Or target a whole file:

bash
$PYTHON $IMPACT /path/to/repo path/to/module.py
2. Read the data, write the summary

The script prints a structured markdown report. Treat it as input for your final summary, not the deliverable. It deliberately doesn't assign a "high/medium/low" risk label — that's your job, after weighing:

  • Refs concentrated in one package (low blast) vs. fanned across many (high)
  • Test refs present (good — the change has a verification surface) vs. absent
  • Doc mentions (renames need to update docs too)
  • Caveats listed at the bottom (what the script can't see)
3. Drill if needed

If a particular package looks suspicious, follow up with tree-sitting to read the actual call sites:

bash
TREESIT=/mnt/skills/user/tree-sitting/scripts/treesit.py
$PYTHON $TREESIT /path/to/repo --no-tree 'source:caller_function'

Options

FlagDefaultPurpose
--features PATH_FEATURES.mdRoot _FEATURES.md — when present, refs get clustered by feature in addition to by package.
--skip DIRS(defaults from tree-sitting)Extra comma-separated dirs to skip.
--limit-per-name N500Cap refs per symbol name. Bump if you suspect truncation.
--jsonoffEmit JSON instead of markdown — for downstream tooling.

Output Sections

# Impact Report: <target>

## Target
  Kind, definition sites with line ranges.

## Direct & Textual References (N total)
  Top-line counts, then refs grouped by:
  - Code references by package
  - Test references
  - Documentation mentions

## Affected Features (from _FEATURES.md)        ← only if file present
  Feature name → ref count + file count.

## Suggested Test Surfaces
  Test files that already reference the target, plus tests neighboring
  the definition. Likely the regression net for the change.

## Caveats
  What the scan can't see (dynamic dispatch, cross-language, cross-repo).
Show full SKILL.md (231 more words)Show less

Composition with Other Skills

  • Run after exploring-codebases if the repo also has a freshly generated _FEATURES.md — the impact report will cluster refs by feature, which makes the blast radius story much more legible than raw package directories.
  • Use tree-sitting to drill specific call sites once impact has identified them.
  • Use searching-codebases when you want regex/AST search over the same corpus rather than impact analysis on a known target.

Honest Limits

  • Text-based ref discovery. Refs are matched by symbol name, not by type-resolved call edges. Common names (run, init, handler) will pick up unrelated symbols. Prefer running this on distinctive names; otherwise expect noise and read the snippets.
  • No type/MRO resolution. Dynamic dispatch (getattr, duck-typed method calls, virtual dispatch in C++) is missed or over-matched.
  • No cross-language tracing. A TS frontend calling a Python backend handler over HTTP appears as zero refs — they're not in the same AST.
  • No cross-repo tracing. Consumers in separate repos (downstream packages, sibling services) are invisible. For multi-repo impact, reach for GitNexus / SourceGraph.
  • No persistent index. Each run re-scans. Fine for single-shot use; acceptable cost (~700ms scan + sub-ms queries) for a few hundred files.
  • Diff input not yet supported. v0.1 takes a symbol or file path. Diff → affected-symbols extraction is a planned follow-up.

Files

  • scripts/impact.py — Single-entry CLI. Resolves target → walks AST refs → augments with text scan → clusters by package and (optionally) by feature → renders markdown or JSON.

© oaustegard, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in assessing-impact of oaustegard/claude-skills.

  • SKILL.md
  • CHANGELOG.md
  • README.md
  • scripts/impact.py

Open the folder on GitHubat commit cf49d47

Compare with similar skills

Assessing Impact next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Assessing Impact compared with similar skills
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Assessing Impact this skilloaustegard/claude-skills150—~1.4kAutomated safety check: PassMIT
Nestjs Best Practicesrolling-scopes/rsschool-app10k6 repos~1.2kAutomated safety check: PassMIT
Guidelinesakash-network/node1.1k20 repos~577Automated safety check: PassMIT
Component Refactoringlangflow-ai/langflow155k—~3.5kAutomated safety check: PassMIT
Migrate Core Code to Submodulestinyhumansai/openhuman42k—~2.6kAutomated safety check: PassGPL-3.0
ast-grep Structural Searchcode-yeongyu/oh-my-openagent70k—~3.3kAutomated safety check: PassMIT

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Questions about Assessing Impact

What does Assessing Impact do?

Pre-change blast-radius report for a symbol or file. An agent skill from oaustegard/claude-skills. Assessing Impact is an agent skill from oaustegard/claude-skills. Pre-change blast-radius report for a symbol or file.

When should I use Assessing Impact?

Assessing Impact fits situations like: about to refactor; delete something in a repo you dont own — what breaks if I change validateUser; is this safe to remove; where is this used.

How do I install Assessing Impact in Claude Code?

Run `npx skills add oaustegard/claude-skills --skill assessing-impact -a claude-code`. Or copy the skill folder (assessing-impact in oaustegard/claude-skills) into .claude/skills/assessing-impact in your project. Claude Code loads it when a task matches its description.

How do I install Assessing Impact in Codex?

Run `npx skills add oaustegard/claude-skills --skill assessing-impact -a codex`. Or copy the skill folder (assessing-impact in oaustegard/claude-skills) into .agents/skills/assessing-impact in your project. Codex loads it when a task matches its description.

Can I use Assessing Impact in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add oaustegard/claude-skills --skill assessing-impact -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/assessing-impact, .gemini/skills/assessing-impact, .github/skills/assessing-impact and .opencode/skills/assessing-impact in your project.

What does Assessing Impact need to run?

Going by SKILL.md and its folder, Assessing Impact needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Assessing Impact access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Assessing Impact safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Assessing Impact use?

Assessing Impact is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Assessing Impact use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Assessing Impact?

Skills that share tags, products or a category with Assessing Impact: Nestjs Best Practices (rolling-scopes/rsschool-app, 10k stars), Guidelines (akash-network/node, 1.1k stars), Component Refactoring (langflow-ai/langflow, 155k stars) and Migrate Core Code to Submodules (tinyhumansai/openhuman, 42k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Assessing Impact?

oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 66 skills in this directory. The repository was last updated on October 8, 2026.

Source: oaustegard/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.