mcpbeat Sign in

Improving Frontend Coverage Agent Skill

Runs frontend unit tests with coverage, analyzes coverage reports, and implements meaningful tests to increase coverage by ~0.2%. Use when you want to systematically improve frontend test coverage with high-value test cases.

928 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
45465
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/streamlit/streamlit --skill improving-frontend-coverage

What it tells the agent to use

found in the instruction text
Task spawns other agents

The instruction itself

4 sections, as written by the author

Improving frontend coverage

Increase frontend unit test coverage by ~0.2% through meaningful tests that add real value.

Be fully autonomous — Do NOT stop or pause to ask for confirmation. Keep iterating (analyze → implement → verify) until the 0.2% coverage target is reached. If you encounter ambiguities about what to test, make a reasonable choice and proceed.

Workflow

Step 1: Run tests with coverage

COVERAGE_JSON=1 make frontend-tests  # ~5 min

Reports generated in frontend/coverage/:

  • coverage-summary.json - Per-file percentages (lines, branches, functions)
  • coverage-final.json - Line-level data with uncovered line numbers (hit count 0 in s, f, b maps)

Step 2: Analyze and prioritize

Read coverage-summary.json to find files with:

  • Large size + below-average coverage (high impact)
  • Core components in lib/src/components/
  • Utility functions in utils/src/

Skip: >97% coverage, auto-generated, .d.ts, test files.

Step 3: Implement tests (in subagent)

Launch a subagent to implement tests for each prioritized file. Provide the subagent with:

  • The target file path and its uncovered lines from coverage-final.json
  • Instructions to read the source, existing tests, and write new tests
  • The test selection guidelines below

The subagent should:

  • Read source and existing tests to understand gaps
  • Write tests for: conditional rendering, event handlers, error states, edge cases, accessibility
  • Follow RTL best practices: query by role/label, test behavior not implementation
  • Run the new tests to verify they pass: cd frontend && yarn test path/to/Component.test.tsx

Step 4: Verify and iterate

cd frontend && yarn test path/to/Component.test.tsx  # Run new tests
COVERAGE_JSON=1 make frontend-tests                   # Measure progress

Repeat steps 2-4 until coverage improves by ≥0.2%, then run make check.

Step 5: Simplify, review, and address feedback

Once all tests pass and coverage target is met:

  • Run the simplifying-local-changes subagent to clean up and simplify the code changes. Wait for completion.
  • Run the reviewing-local-changes subagent to review the changes. Wait for completion and read the review output.
  • Address the review feedback: for each recommendation, implement it if valid and improves code quality; skip with brief reasoning if not applicable or would over-engineer.
  • Run /checking-changes to verify everything still passes after changes.

Test selection

DO test: Conditional rendering, user interactions, prop variations, error handling, accessibility, edge cases (null, empty, max values).

DON'T test: Pass-through props, styling, library internals, implementation details, already well-covered code.

Coverage exclusions: Use /* istanbul ignore next */ sparingly for code that genuinely doesn't need testing. Always include a reason (e.g., /* istanbul ignore next -- defensive */):

  • Browser-specific branches that can't run in jsdom (/* istanbul ignore next -- browser-only */)
  • Defensive fallbacks that should never execute (/* istanbul ignore next -- defensive */)
  • Framework-required boilerplate (/* istanbul ignore next -- exhaustive */)

Notes

  • Quality > coverage numbers - skip tests that don't catch real bugs
  • Test files: co-located as <Component>.test.tsx
  • Use /checking-changes after implementing tests

Other skills for the same job

different authors, same section of the catalogue
Webapp Testing
by anthropics
vendor ×12

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

6k tokens scripts
Finishing A Development Branch
by ZhanlinCui
×7

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

1k tokens
Test Driven Development
by w95
×7

Use when implementing any feature or bugfix, before writing implementation code

2k tokens
Systematic Debugging
by ratacat
×7

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

10k tokens scripts
Verification Before Completion
by ZhanlinCui
×6

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

1k tokens
Backtest Expert
by BaggaT236
×3

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

15k tokens scripts
Adaptyv
by christophacham
×3

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

16k tokens
Aeon
by christophacham
×3

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

19k tokens

How to use it

Copy the folder

Take streamlit/improving-frontend-coverage from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.