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Agent skill

Predict

by softspark in softspark/ai-toolkit

Analyzes diffs for regression risk and blast radius, generates risk-scored impact report.

Apache-2.0Auto-check passedDevelopment

Install Predict

skills CLI
$ npx skills add softspark/ai-toolkit --skill predict -a claude-code

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

GitHub CLI
$ gh skill install softspark/ai-toolkit predict --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/softspark/ai-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/app/skills/predict .claude/skills/predict && 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
predict
GitHub stars
179
Token cost
~1.2k tokens
SKILL.md length
479 words
Files
1
Skills in repo
112
Repo updated
First seen
Licence
Apache-2.0

At a glance

Analyzes diffs for regression risk and blast radius, generates risk-scored impact report.

  • Works in 4 steps: Scope: Identify Target Files → Trace: Build Dependency Graph → Assess: Calculate Risk Score → …
  • Tasks that involve Pull requests
  • SKILL.md covers Usage, Protocol, Rules and Gotchas, plus 1 more section
  • Calls git

What it does

Predict is an agent skill from softspark/ai-toolkit. Analyzes diffs for regression risk and blast radius, generates risk-scored impact report. Triggers: PR review, code change risk, breaking change, blast radius, regression check.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Pull requests. The repository describes itself as: Professional-grade AI coding toolkit: 94 skills, 44 agents, multi-platform (Claude, Cursor, Windsurf, Copilot, Gemini, Cline, Roo Code, Aider, Augment, Antigravity, Codex CLI… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Pull requests

Example prompts

  • “Use the predict skill to analyz diffs for regression risk and blast radius, generates risk-scored impact report”
  • “/predict”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob

Workflow steps

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

  1. Scope: Identify Target Files
  2. Trace: Build Dependency Graph
  3. Assess: Calculate Risk Score
  4. Report: Generate Impact Prediction

What it can do on your machine

Read from SKILL.md and the folder at commit d64db2b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, 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

Predict loads about 1.2k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 479 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from softspark/ai-toolkit at commit d64db2b, republished under its Apache-2.0 licence (© softspark). 479 words, ~1,153 tokens.

Download SKILL.mdSave it as .claude/skills/predict/SKILL.md (or your agent's skills folder).
name
predict
description
Analyzes diffs for regression risk and blast radius, generates risk-scored impact report. Triggers: PR review, code change risk, breaking change, blast radius, regression check.
allowed-tools
Read, Grep, Glob
effort
medium
disable-model-invocation
true
argument-hint
[change description]
agent
predictive-analyst
context
fork

Predict Command

$ARGUMENTS

Triggers the Predictive Analyst to assess the impact and regression risk of proposed changes.

Usage

bash
/predict [path_or_diff]
# /predict src/auth              : analyze all files under src/auth
# /predict --diff                : analyze uncommitted changes (git diff)
# /predict src/api/routes.ts     : analyze a single file

Protocol

1. Scope: Identify Target Files
  • If path provided: collect all files under that path
  • If --diff: run git diff --name-only to get changed files
  • List each file with its last-modified date and line count
2. Trace: Build Dependency Graph

For each target file, find dependents:

bash
# Find files that import/require the target
grep -rl "import.*from.*[target]" --include="*.ts" --include="*.py" --include="*.js" .
grep -rl "require.*[target]" --include="*.js" --include="*.ts" .

Build a graph: changed file, direct dependents, transitive dependents (1 level)

3. Assess: Calculate Risk Score

Score each changed file on a 1 to 5 scale:

FactorWeightScoring
Dependent count30%0 deps = 1, 1 to 3 = 2, 4 to 10 = 3, 11 to 20 = 4, 21+ = 5
Test coverage30%Has dedicated test = 1, partial = 3, none = 5
Change surface20%< 10 lines = 1, 10 to 50 = 2, 50 to 200 = 3, 200+ = 5
Shared/core file20%Leaf = 1, mid-layer = 3, core/shared = 5

Overall risk = weighted average rounded to nearest integer.

4. Report: Generate Impact Prediction

Output a markdown report:

markdown
## Impact Prediction: [scope]

| File | Risk | Dependents | Test Coverage | Notes |
|------|------|------------|---------------|-------|
| src/auth/login.ts | 4/5 | 12 files | partial | Core auth flow |

### High-Risk Changes (score >= 4)
- [file]: [why it's high risk and what to watch]

### Recommended Actions
- [ ] Add tests for [untested file]
- [ ] Review [high-dependent file] with extra scrutiny
- [ ] Run integration tests covering [affected area]

Rules

  • MUST base risk scores on measurable signals (dependent count, coverage, diff size) — not vibes or adjective scales
  • MUST name at least one specific action per high-risk file — "review carefully" is not an action
  • NEVER predict regressions beyond what the signals justify. A single file with 20 dependents is a signal; a generic "this might break things" is noise.
  • NEVER skip the test-coverage factor — a high-dependent file with 100% coverage is lower risk than a low-dependent file with none
  • CRITICAL: the report ranks files by weighted risk score, not alphabetically. Readers will stop after the first 5 entries.
  • MANDATORY: state the confidence level explicitly. Predictions from a 5-line diff are HIGH confidence; predictions from 500-line refactors are LOW.
Show full SKILL.md (195 more words)Show less

Gotchas

  • grep -rl "import.*from.*[target]" is easily fooled by comments and string literals. Use the language's real AST tools (ts-morph, ast-grep, pyflakes) for accurate dependency graphs on anything beyond trivial diffs.
  • Dynamic imports (importlib.import_module, require(variable), JavaScript await import()) are invisible to grep. Flag explicitly when the target uses them.
  • Test coverage reported by CI may exclude generated code, migrations, and __init__.py. "Has dedicated test = score 1" assumes a real assertion exists — check the test file rather than just the path match.
  • A 5-line diff in a "core" file is often more dangerous than a 500-line diff in a leaf file. The change_surface weight alone is misleading; combine with shared/core weight for meaningful signals.
  • Predictions about regressions are calibrated against the current test suite, not unknown production behaviors. A "low-risk" verdict means "tests likely pass", not "users will not notice".

When NOT to Use

  • For executing a change after prediction — use /fix, /refactor, or the relevant skill
  • For PR review of logic quality — use /review
  • For CI pipeline risk analysis — use /ci-cd-patterns
  • For code quality metrics (complexity, duplication) — use /analyze
  • For a brand-new codebase with no change history — this skill needs dependents to measure; use /explore first

© softspark, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in app/skills/predict of softspark/ai-toolkit.

Open the folder on GitHubat commit d64db2b

Compare with similar skills

Predict 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.

Predict compared with similar skills
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Predict this skillsoftspark/ai-toolkit179—~1.2kAutomated safety check: PassApache-2.0
Finishing a Development Branchobra/superpowers296k5 repos~1.9kAutomated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Check PRonyx-dot-app/onyx32k2 repos~2.3kAutomated safety check: PassMIT
Understand Diff AnalysisEgonex-AI/Understand-Anything85k1 repos~1.4kAutomated safety check: PassMIT
PR Design DocOpenHands/OpenHands90k—~2.4kAutomated safety check: PassMIT

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Categories

Questions about Predict

What does Predict do?

Analyzes diffs for regression risk and blast radius, generates risk-scored impact report. Predict is an agent skill from softspark/ai-toolkit. Analyzes diffs for regression risk and blast radius, generates risk-scored impact report.

When should I use Predict?

Predict fits situations like: tasks that involve Pull requests.

How do I install Predict in Claude Code?

Run `npx skills add softspark/ai-toolkit --skill predict -a claude-code`. Or copy the skill folder (app/skills/predict in softspark/ai-toolkit) into .claude/skills/predict in your project. Claude Code loads it when a task matches its description.

How do I install Predict in Codex?

Run `npx skills add softspark/ai-toolkit --skill predict -a codex`. Or copy the skill folder (app/skills/predict in softspark/ai-toolkit) into .agents/skills/predict in your project. Codex loads it when a task matches its description.

Can I use Predict 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 softspark/ai-toolkit --skill predict -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/predict, .gemini/skills/predict, .github/skills/predict and .opencode/skills/predict in your project.

What does Predict need to run?

Going by SKILL.md and its folder, Predict needs the command-line tools its instructions call (git). Its frontmatter pre-approves these tools: Read, Grep, Glob.

Does Predict access the network?

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

Is Predict 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. Review the folder before installing.

What licence does Predict use?

Predict is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Predict use?

About 1.2k tokens (SKILL.md is roughly 4.6k 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 Predict?

Skills that share tags, products or a category with Predict: Finishing a Development Branch (obra/superpowers, 296k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars), Check PR (onyx-dot-app/onyx, 32k stars) and Understand Diff Analysis (Egonex-AI/Understand-Anything, 85k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Predict?

softspark (a GitHub user) maintains it in softspark/ai-toolkit, which has 179 GitHub stars. The repository holds 112 skills in this directory. The repository was last updated on October 7, 2026.

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