Agent skill

Meticulous Increase Coverage

by FlintSH in FlintSH/Flare

Increase coverage for a Meticulous project by tracing specific under-covered files back to a real UI action in the codebase, driving that action with a real recorded browser session, and validating…

MITAuto-check passedProductivity & Automation

Install Meticulous Increase Coverage

skills CLI
$ npx skills add FlintSH/Flare --skill meticulous-increase-coverage -a claude-code

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

GitHub CLI
$ gh skill install FlintSH/Flare meticulous-increase-coverage --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/FlintSH/Flare.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/meticulous-increase-coverage .claude/skills/meticulous-increase-coverage && 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
meticulous-increase-coverage
GitHub stars
135
Token cost
~7k tokens
SKILL.md length
4,012 words
Files
2 (incl. references)
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Increase coverage for a Meticulous project by tracing specific under-covered files back to a real UI action in the codebase, driving that action with a real recorded browser session, and validating…

  • Works in 9 steps: Baseline coverage → Separate dead code from real targets → Trace, don't guess → …
  • Asked to increase coverage
  • SKILL.md covers What you deliver, Before you start: run this on…, Step 1 — Baseline coverage and Step 2 — Separate dead code…, plus 8 more sections
  • Calls git

What it does

Meticulous Increase Coverage is an agent skill from FlintSH/Flare. Increase coverage for a Meticulous project by tracing specific under-covered files back to a real UI action in the codebase, driving that action with a real recorded browser session, and validating the improvement with a clean coverage comparison. Also opens a PR proposing .meticulousignore entries for code that structurally never executes in-browser. Use when asked to "increase coverage", "find untested code", or "add .meticulousignore entries" for a project.

Its SKILL.md is about 7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/worked-example.md`).

It sits in Productivity & Automation, covering Test coverage and Browser automation. The repository describes itself as: A modern, lightning-fast file sharing platform built for self-hosting. Created with support for ShareX, KDE Spectacle, Flameshot, and easy to set up. The licence is MIT.

When your agent uses it

  • Asked to increase coverage
  • Find untested code
  • Add .meticulousignore entries for a project

Example prompts

  • “increase coverage”
  • “find untested code”
  • “add .meticulousignore entries”
  • “/meticulous-increase-coverage”

Workflow steps

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

  1. Baseline coverage
  2. Separate dead code from real targets
  3. Trace, don't guess
  4. Drive the flow
  5. Session-time budget and close discipline
  6. Collect the session ids and trigger the test run
  7. Compare with a union, not a raw diff
  8. Verify and report
  9. Open the .meticulousignore PR

What it can do on your machine

Read from SKILL.md and the folder at commit c910523. 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

    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

Meticulous Increase Coverage loads about 7k tokens when it runs, and up to ~8.2k if it reads all its reference files. Until then it costs about 123 tokens; SKILL.md has 4,012 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~123
When it runs · the whole SKILL.md, loaded when a task matches
~7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8.2k

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 FlintSH/Flare at commit c910523, republished under its MIT licence (© FlintSH). 4,012 words, ~6,974 tokens.

Download SKILL.mdSave it as .claude/skills/meticulous-increase-coverage/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
meticulous-increase-coverage
description
Increase coverage for a Meticulous project by tracing specific under-covered files back to a real UI action in the codebase, driving that action with a real recorded browser session, and validating the improvement with a clean coverage comparison. Also opens a PR proposing .meticulousignore entries for code that structurally never executes in-browser. Use when asked to "increase coverage", "find untested code", or "add .meticulousignore entries" for a project.
user-invocable
true

Increase coverage for a Meticulous project

Run meticulous-cli-update first if you haven't already this conversation (it also covers authentication and project selection).

What you deliver

Two separate outputs, both expected — neither substitutes for the other:

  1. One or more test runs from newly recorded sessions that provably extend coverage. "Provably" means a comparison against the baseline naming the files whose coverage went up, and by how much (Step 7). If a target turns out not to be coverable, say so rather than padding the list.
  2. A PR proposing .meticulousignore changes. Only include paths — most often whole directories — that you are confident are not coverable at all. Anything you merely failed to reach in one sitting does not belong there; leave it out and mention it in the PR description instead.

Before you start: run this on main, with a clean tree

Every command below relies on the CLI resolving things from your local checkout: js-coverage defaults to the current git HEAD, trigger-test-run defaults to HEAD for the deployment and to the merge-base with the origin default branch for the base. On main with a clean tree those collapse to a single commit, which is exactly what you want — no diff, a head-only run, and a union in Step 7 that the API will actually accept.

Off main this breaks in ways that are tedious to unpick: union coverage is rejected unless every run executed the exact same commit, and a PR's merge commit is recomputed whenever its base branch moves, so a run triggered earlier against a since-advanced base no longer unions with a new one.

So: check out main, pull, and make sure git status is clean before Step 1.

Then confirm there is actually a test run to work from:

bash
meticulous agent test-run-for-commit

Keep the id it prints — Step 7 falls back to it. If it reports "No test run found for commit …", stop and report that to the user; you cannot baseline without it. The most common cause is the CLI pointing at the wrong project, so suggest they check with meticulous auth get-project. meticulous auth set-project only applies for OAuth tokens; API tokens are bound to one project (so set-project fails), and injected credentials leave no local token to select — in those cases the fix is a different credential, not set-project.

Step 1 — Baseline coverage

bash
meticulous agent js-coverage --includeAllFiles --includeCoveragePercentage \
  > /tmp/baseline-coverage.tsv

If this reports "No test run found for commit …" (it shouldn't, if the check above passed), stop and report to the user. Do not work around it by baselining against some other commit's run: Step 7's union requires your new run and the baseline to have executed the same commit.

The base run's sessions often haven't all been replayed yet, which understates its coverage — if js-coverage says so, run meticulous agent complete-base-run (it waits by default until nothing more can be scheduled; it can take a while, so check back or re-run rather than assuming it hung), then re-run js-coverage. Don't expect unexecutedSessionCount to always reach 0 — some sessions can be permanently unobtainable, and js-coverage tolerates a small share of those rather than refusing forever.

Step 2 — Separate dead code from real targets

You are looking for two different things in this file, and it helps to keep them apart:

  • .meticulousignore candidates — files that are uniformly at 0% across a whole directory, which suggests they never execute in a browser at all.
  • Coverage targets — files a real user flow could reach but no recorded session happens to. These are not only the 0% files. A file at 12% or 40% usually means one path through it runs and the rest doesn't, and those partial files are often the cheapest wins: the module already loads, so a single extra interaction can light up a large block. Sort ascending by percentage and work up from the bottom, rather than stopping at 0%. Some 0%/low files are gated behind a feature toggle that's off by default rather than a UI path nobody's driven — check the toggle registry and the file's gating condition before assuming it needs a brand-new flow, since flipping the toggle on locally can turn a dead-looking file into an easy target.

Start with the ignore candidates, since they shrink the list. Break the 0%-coverage files down by top-level directory, so you are reasoning about groups rather than 100s of individual files. The exact command depends on how the repo is laid out — a monorepo wants the first two path segments, a single-app repo wants something deeper. For example, in a packages/<name>/… monorepo:

bash
# example only — adjust the segment depth to this repo's layout
awk -F'\t' 'NR>1 && $2=="0.0" {split($1,a,"/"); print a[1]"/"a[2]}' \
  /tmp/baseline-coverage.tsv | sort | uniq -c | sort -rn

A directory where every single file is at 0% (not just some) is a strong signal it never ships to the browser (backend, CLI tooling, docs, e2e test harness). Those are your .meticulousignore candidates.

There is a second, stronger signal that doesn't depend on coverage data at all and catches individual dead files scattered inside an otherwise-live directory, which the uniformly-0% heuristic above misses entirely. For any file sitting at 0%, grep the codebase for its actual exported symbol — not just its filename:

bash
# example only — adjust the source root and extensions to this repo
grep -rn "theActualExportedName" <src-root> --include="*.ts" --include="*.tsx"

If the only match is the file's own definition, nothing imports it, so no session — however comprehensive — can ever execute it. That is proof of unreachability, not an inference from silence, and it is worth checking even when you already have a directory-level rule elsewhere in this file: dead exports accumulate inside packages that are otherwise very much alive.

Some categories are safe exclusions almost everywhere and are worth proposing without further tracing, provided the coverage data agrees they are uniformly 0%:

  • test files and their directories — __tests__/, __mocks__/, *.test.*, *.spec.*
  • Storybook — *.stories.*, __stories__/, .storybook/
  • test/mock harness directories — testing/, mocks/, fixtures
  • build, lint and codegen config executed only by Node — *.config.*, setupTests.*, scripts directories

Note that some of these may already be outside the coverage report entirely; check the baseline before adding a rule that does nothing.

Be suspicious of a directory showing 0% everywhere if you know it is bundled into the frontend (a shared component/utils library the main app imports). That pattern is more likely a source-map/path-attribution gap than genuinely dead code — leave it out of the ignore list and flag it as unresolved.

Now pick the coverage targets. Filter the generated/config noise out of the real app package first, then order what's left by how little of it runs — keeping the partially-covered files in, not just the 0% ones. The patterns are repo-specific; inspect the actual paths in your baseline rather than copying this verbatim:

bash
# example only — derive the patterns from the paths this repo actually has
grep -v "/__tests__/\|\.test\.\|\.stories\.\|/testing/\|/mock" \
  /tmp/baseline-coverage.tsv | sort -t$'\t' -k2 -g > /tmp/candidates.tsv

Group the candidates by feature area rather than picking the single worst files: one recorded flow usually moves a whole cluster of related files at once, so a directory sitting at 5-20% across a dozen files is a better target than an isolated 0% file behind an obscure branch.

Step 3 — Trace, don't guess

For each candidate file, find its actual caller(s) — for example:

bash
# example only — adjust the source root and extensions to this repo
grep -rln "<ExportedThing" <src-root> --include="*.tsx" | grep -v test

Read the caller. Confirm:

  • It's reachable via a simple, describable UI action (a specific button, a specific menu item) — not buried behind a feature flag, a disabled config (e.g. billing/SSO toggles that are off in this environment), or a conditional branch that only fires for certain object types.
  • If the target is a hook, check every branch that calls it. Hooks are often called conditionally — one branch might route through a completely different mechanism (a plain router <Link> instead of the app's own navigation hook, a side-panel open instead of a full navigate). Confirm which branch your candidate action actually hits.

Step 4 — Drive the flow

Any of these three drivers records correctly — verified against two different apps:

  • Claude in Chrome — the only one that drives the user's own signed-in Chrome profile, so an authenticated app needs no login flow. Its input path is also the one that wedges (see below), so verify early and be ready to switch.
  • Playwright and agent-browser — CDP-launched browsers, faster and more scriptable, and reliable in every test here. The trade-off is a fresh profile each time, so you have to sign in. agent-browser additionally refuses a click when the target is covered by another element, naming the covering node, which catches a class of silent mis-click the other two will happily perform.

Set a realistic viewport whichever you pick. The CDP browsers default to something small (around 1280px wide) where a real Chrome window is often twice that. Responsive layouts render different components at different widths, so the default viewport can quietly cover different code — or hide the control you were aiming for.

What matters far more than the choice of tool is the one rule below.

Only trusted events are recorded. The recorder ignores anything synthesised in page JS, so element.click(), assigning input.value, or dispatching your own events all drive the app convincingly and record nothing. The page looks right, the session comes back empty. Drive everything through the tool's real input actions.

When something doesn't take effect, find out which half is broken before changing tactics — install a capturing probe and repeat the action:

js
window.__ev = []
;['pointerdown', 'click', 'keydown', 'change'].forEach((t) =>
  window.addEventListener(
    t,
    (e) => window.__ev.push({ t, trusted: e.isTrusted }),
    true
  )
)
  • nothing captured → your input never reached the page; a different selector or coordinate won't help (see the wedged-extension note below)
  • captured but trusted: false → it reached the page but will not be recorded; you are synthesising somewhere
Three ways an action records as nothing

All three look like success in the browser, which is what makes them expensive — you find out from the coverage numbers, long after the fact.

Native <select>s. Setting the value through a form-fill action, or assigning it in JS, fires a change with isTrusted: false — the app reacts and the value visibly updates, so it looks like it worked, but the recorder ignores it and the sort/filter never happens on replay. Clicking the <select> is no good either: that opens an OS-level popup the driver can't see. What works is to focus the element and press the first letter of the option's visible text ("p" → "Priority"), which yields a trusted keydown and a trusted change. Repeat the letter to cycle options sharing an initial. Verify with a change listener reading e.isTrusted — the value updates either way, so the value alone tells you nothing.

Modifier shortcuts. Replay reproduces a modifier only if a discrete modifier keydown was recorded and is still held. Some drivers send one only for the base key: Claude in Chrome's cmd+k and agent-browser's press Alt+ArrowRight both record a single keydown with the modifier flag set and no separate modifier press, so on replay the flag is cleared and the handler body never runs — while working perfectly live. Playwright's press('Alt+ArrowRight') does record the discrete press and replays correctly (verified by coverage).

So: prefer the equivalent click target where one exists, and if you must use a chord, drive it with Playwright and confirm from coverage afterwards. If the line holding if (… && event.metaKey) is covered but the body is not, the keydown was delivered and the condition evaluated false — that is this.

Double-clicks. A double-click may be recorded as a single click, in which case the replay never fires onDoubleClick and every later event in that session targets UI that never opened — so coverage drops. Check the recorded event count looks like two press/release pairs, and treat any double-click-only feature as suspect until coverage confirms it.

Some interactions may not survive agent-driven recording at all

Occasionally an interaction records cleanly and visibly works live, but the handler it's meant to trigger never fires on replay — with no error, and the affected file sitting at exactly its baseline percentage in Step 7's union. One case seen: typing a value into an input inside a dropdown's own portal-rendered content (a filter chip, a view rename behind a "..." menu). Plain clicks in the same portal, and the identical type-then-Enter sequence on an input in the main page tree, both replay fine — so this is specific to keyboard/text input inside a portal, not a driver issue.

Don't assume a typed-value target worked just because the live interaction did — check Step 7's diff. If a target only reproduces through this kind of interaction and won't move, that's a shortcoming of agent-driven recording for this flow: report it as unresolved and suggest a human drive that one flow manually, rather than continuing to pad the list with retries.

claude-in-chrome specifics
  • Screenshots are downscaled (~0.6x), so they are not CSS pixels. Click coordinates read off the screenshot, or scale a getBoundingClientRect() centre by screenshotWidth / window.innerWidth. Re-derive after any resize, and re-screenshot rather than reusing coordinates from an earlier page — layout shifts, and a stale coordinate can land on the wrong element and record an interaction you did not intend.
  • Re-acquire a ref immediately before clicking it, and never reuse one across pages or tabs. Don't predict a number — read_page does not emit them in order. Refs and coordinates are equally reliable; pick whichever is convenient. This is not unique to claude-in-chrome — agent-browser's snapshot refs go stale the same way, and reusing one silently clicks whatever now occupies that ref, not what you intended. It cost a real mistake once: a stale ref landed on a table's "Add New" affordance and created a blank record. Take a fresh snapshot immediately before every click when the DOM might have changed, and treat an unexpected page/record-count change right after a click as a sign a ref just misfired, not as an unrelated bug — clean up whatever it created before continuing.
  • Input delivery wedges intermittently. Every click and keystroke reports success, reads keep working, and nothing reaches the page. Refs and coordinates die together, so this is never a selector problem — and it is not cleared by a new tab, a fresh navigation, waiting, or retrying. A full Chrome restart helps but does not durably fix it. Check the probe after your first interaction, before driving a whole flow, and if input isn't landing switch to Playwright or agent-browser rather than switching selector method. Both stayed reliable throughout, including on the same page at the same moment that Claude in Chrome was dead.
Show full SKILL.md (1,699 more words)Show less
Drive it, then verify
  1. Navigate to the target URL and drive the real action.
  2. Confirm it worked against the DOM (e.g. document.body.innerText.includes(...)), not just a screenshot — a tooltip appearing can look like success. Check you are still on the page you think you are: an app that has quietly redirected you to a login screen will absorb blind coordinate clicks into empty space and hand you a session with zero events.
  3. Close the tab.

Then sanity-check the recording, before you trigger anything. Wait ~10s after closing the tab, so the session is complete, and check that it captured something:

bash
meticulous agent sessions --limit 10 --excludeSyntheticSessions \
  --includeDurationSeconds --includeNumberUserEvents \
  --includeNumberUrlsVisited --includeStartUrl --includeAbandonedReason

Read the row you just produced:

  • no row at all — nothing was uploaded yet; wait a little longer before concluding the recording failed
  • numberUserEvents of 0 — the recorder saw no user input. Your clicks were not reaching the page, or were synthesised rather than trusted; go back to the input-delivery probe above. Replaying this session is pointless.
  • numberUrlsVisited of 1 when you navigated several times — the later pages did not make it into this session. They either landed in their own sessions (fine, collect those ids too) or were swallowed as an unreplayable tail (see the hard-navigation note in Step 5).
  • durationSeconds over 300 — everything past the 5-minute mark will be silently trimmed on replay (Step 5). Re-record the overflowing part as its own session rather than hoping it survives.
  • populated abandonedReason — the recorder gave up on the session (see the 10-minute cap in Step 5); it is not worth replaying.
  • startUrl that is not the page you drove — the navigation you cared about belongs to a different session than you assumed.

A session is only complete once its tab is closed. While the tab is open the row reflects only the chunks uploaded so far, so a low or zero numberUserEvents there means "not flushed yet", not "the recording failed". A session measured for this skill read 0 events with the tab open and 12 once it was closed. Judging it early nearly caused a perfectly good recording to be re-driven from scratch.

Events upload on a short interval (a few seconds), but anything still unflushed at unload is only stashed in sessionStorage and re-sent on a later page load to the same origin — so a session's tail can be delayed until the next visit. Prefer navigating away over hard-closing the browser, and never judge a recording immediately.

Recording several targets in one sitting? Run this check after each one, not just once at the end. Checking only at the end makes it impossible to tell which action lost a session, and you'll have to re-drive all of them just to find out which one needs redoing.

Step 5 — Session-time budget and close discipline

  • Cloud replays cap at 5 minutes of session time. Everything recorded after that is silently trimmed from the replay — the run still succeeds and reports itself accurate, so the loss is invisible unless you look for it (snapshot routes stop early; far fewer allowed events than the session has clicks). Don't leave this to feel: agent sessions --includeDurationSeconds gives you the number, and anything over 300 is losing its tail.
  • Your interaction pace eats this budget. Each find/click/verify round trip is 10-60s of recorded session time. Plan the flow completely before opening the tab, batch your actions into as few round trips as possible with short waits between them, verify from the recording afterwards rather than mid-flow, and aim to stay under 4 minutes. Several short sessions beat one long sweep.
  • Direct URL navigation is a legitimate fast path to each target page and replays fine — prefer it over slow click-paths. But hard navigations split the recording into multiple sessions, so collect every resulting session id afterwards and pass them all to --sessionIds (Step 6). Mostly this is fine, each piece staying under the replay cap. The trap is navigating again too quickly: a page reached a second or two after the previous one gets appended as the tail of that session instead of starting its own, and tails frequently do not replay — so the page renders perfectly while you drive it and still contributes no coverage. Give each page you actually care about its own dwell time (~10s) before moving on, and check in Step 6 that it shows up as a startUrl in its own right. The same caution applies to a plain <form> submit with no wired onSubmit handler — it triggers a real browser reload rather than an SPA transition, and can just as easily drop the just-recorded, unflushed session if you navigate on immediately afterward.
  • Recorder limits: a 10-minute hard cap on tab-open time marks the whole session "abandoned"; uploads flush on a 5s interval — wait ~6-8s after the last interaction before closing the tab.

Step 6 — Collect the session ids and trigger the test run

First list what you actually recorded, newest first:

bash
meticulous agent sessions --limit 20 --excludeSyntheticSessions \
  --includeDurationSeconds --includeNumberUserEvents \
  --includeNumberUrlsVisited --includeStartUrl

Skip any row with numberUserEvents of 0 — it will replay as nothing and only dilutes the run. Note any row with durationSeconds over 300: it will replay, but only its first five minutes, so treat coverage from its tail as absent rather than assuming the whole flow ran.

Identify your sessions by recorded-at time and startUrl. Be careful here: other people — and other apps pointed at the same project — record too, so never assume the newest N rows are yours. --recordedSince and --visitedUrlFilter are the quickest way to narrow it down when the list is busy.

Expect more sessions than pages you drove: a hard navigation usually ends one session and starts another, so a five-page sweep can produce five ids. Collect all of them. A page whose URL never shows up as a startUrl was probably swallowed as the tail of the previous session and will not replay — re-record it on its own if you need it covered.

Then trigger:

bash
meticulous agent trigger-test-run --sessionIds "<id1>,<id2>,..."

Step 7 — Compare with a union, not a raw diff

bash
meticulous agent js-coverage --headPlusTestRunIds "<newRunId>" \
  --includeAllFiles --includeCoveragePercentage > /tmp/combined-coverage.tsv

This unions your new run into the baseline run resolved from HEAD — the same run Step 1 used — so it is baseline coverage plus your new sessions' coverage. Commit resolution skips runs over an explicit session set, so the run you just triggered won't be picked as the baseline. The union is needed because --sessionIds replaced the selected set for that run rather than adding to it, so your run on its own covers far less than the baseline and a raw diff would read as mass regressions. Diff the union against /tmp/baseline-coverage.tsv: you should see zero regressions, and only the files your new flow touched improve.

Pass only your new run — a run cannot be unioned with itself.

Two signs HEAD resolved to something other than the golden-set run: it is rejected with "is the run being queried", or every file has dropped (which means you unioned into another narrow session set, not a regression). The most likely cause is a pinned-session run predating the skip. Either way, name both sides explicitly, using the baseline id from Step 0:

bash
meticulous agent js-coverage --testRunIds "<baselineRunId>,<newRunId>" \
  --includeAllFiles --includeCoveragePercentage > /tmp/combined-coverage.tsv

If the union is rejected because the runs executed different commits, that is the main/clean-tree precondition biting — see the top of this skill.

Step 8 — Verify and report

For each traced target file: did coverage move? For each presumed-dead file (the .meticulousignore candidates from Step 2): did it stay at 0% in the union comparison (confirming it's genuinely unreachable)?

If a well-traced target didn't move, don't assume the recording failed — re-check the session first (Step 4: does it exist, did it capture user events and URL visits, is it abandoned, is its startUrl the page you drove?), then re-check whether the click actually goes through the file you expected (Step 3) rather than a sibling/parent component. Report honestly if a target remains unresolved; don't claim success without the coverage number to back it.

When you report the gains, be clear about what they are not yet: the test run proves the coverage is reachable, but the project's own coverage figure will only improve once the next session selection picks these new sessions up into the selected set. Until then nothing changes for recurring runs.

Step 9 — Open the .meticulousignore PR

The second deliverable. Branch, commit the .meticulousignore change, and open a PR.

Only propose paths you are confident are not coverable at all. The bar is "no session could ever execute this", not "I didn't get to it today". Prefer directory-level rules over long lists of individual files — a directory rule stays correct as files are added, whereas a file list silently goes stale. In practice most entries come from the safe-exclusion categories in Step 2 plus whatever whole non-browser packages the baseline showed at a uniform 0%.

Confirm before you commit: every path you are about to ignore stayed at 0% in the Step 7 union. A path your own new sessions just covered obviously does not belong in the ignore list, and that check catches it.

A common structure is "ignore everything, then un-ignore what does run in the browser" — the pattern Meticulous's own monorepo uses:

# Ignore everything except packages that are executed in the
# browser and have meaningful frontend coverage.

packages/*
!packages/<frontend-app>/
!packages/<frontend-app>/**
!packages/<shared-ui-lib>/
!packages/<shared-ui-lib>/**

Note that .meticulousignore follows gitignore semantics, so a file cannot be re-included once its parent directory is excluded — un-ignore the directories (!some/dir/**/) as well as the files.

In the PR description, give the reasoning for each rule — why this code cannot run in a browser (it's a Node-only build script, a test harness, a backend package). The baseline can only show you that something is at 0% today, which is never proof it is unreachable, so the justification has to come from what the code actually is. Also call out explicitly:

  • anything you left out of the ignore list despite low coverage because you suspect a source-map/attribution gap rather than dead code (Step 2)
  • anything unreachable only because of environment or feature-flag config rather than structurally — that is the reviewer's judgement call, not yours, so flag it instead of silently ignoring it

Reference

references/worked-example.md runs the whole skill against a small app (kanban-demo), with the real coverage deltas. Worth reading for calibration: it has no 0% files at all, one target that gained coverage and one that recorded cleanly and then failed to replay — and it shows how to tell the difference from executed ranges.

© FlintSH, 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 1 other file (references) in .agents/skills/meticulous-increase-coverage of FlintSH/Flare.

  • SKILL.md
  • references/worked-example.md

Open the folder on GitHubat commit c910523

Compare with similar skills

Meticulous Increase Coverage 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.

Meticulous Increase Coverage compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Meticulous Increase Coverage this skillFlintSH/Flare135—~7kAutomated safety check: PassMIT
Dev-Browser CLI AutomationSawyerHood/dev-browser6.7k1 repos~455Automated safety check: PassMIT
VerifyWeZZard/jlens-qwen36402—~684Automated safety check: PassApache-2.0
QAblueberrycongee/termcanvas406—~830Automated safety check: PassMIT
Dotnet Testingnovotnyllc/dotnet-artisan233—~972Automated safety check: PassMIT
Test Automationrevfactory/harness-1001.3k—~1.7kAutomated safety check: PassApache-2.0

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More from FlintSH/Flare

All 10 skills in this repo
  • Meticulous CLI

    FlintSH/Flare

    Overview of the Meticulous CLI tool and its global options. An agent skill from FlintSH/Flare.

    135 GitHub stars~1.4k tokensUpdated 3 days ago
    Auto-check passed
  • Meticulous Fix

    FlintSH/Flare

    Fix the visual diffs that have been reviewed and rejected on a Meticulous test run, following their review comments if given.

    135 GitHub stars~2.3k tokensUpdated 3 days ago
    Auto-check passed
  • Iterative frontend development loop using Meticulous for per-step visual validation.

    135 GitHub stars~1.3k tokensUpdated 3 days ago
    Auto-check passed
  • Meticulous Review

    FlintSH/Flare

    Analyze a completed Meticulous test run — compare the diffs against the PR description to see what's expected, then focus on finding and flagging potential regressions.

    135 GitHub stars~2.3k tokensUpdated 3 days ago
    Auto-check passed
  • Run a Meticulous session simulation against a live URL and analyze the visual output — either by inspecting screenshots directly (quick-check mode) or by comparing pixel and HTML diffs against a…

    135 GitHub stars~1.8k tokensUpdated 3 days ago
    Auto-check passed
  • Meticulous Test

    FlintSH/Flare

    Run a Meticulous test run after implementing a frontend change, then hand off to the meticulous-review skill to classify each visual change as intended or unintended.

    135 GitHub stars~1.2k tokensUpdated 3 days ago
    Auto-check passed

Questions about Meticulous Increase Coverage

What does Meticulous Increase Coverage do?

Increase coverage for a Meticulous project by tracing specific under-covered files back to a real UI action in the codebase, driving that action with a real recorded browser session, and validating…. Meticulous Increase Coverage is an agent skill from FlintSH/Flare. Increase coverage for a Meticulous project by tracing specific under-covered files back to a real UI action in the codebase, driving that action with a real recorded browser session, and validating the improvement with a clean coverage comparison.

When should I use Meticulous Increase Coverage?

Meticulous Increase Coverage fits situations like: asked to increase coverage; find untested code; add .meticulousignore entries for a project.

How do I install Meticulous Increase Coverage in Claude Code?

Run `npx skills add FlintSH/Flare --skill meticulous-increase-coverage -a claude-code`. Or copy the skill folder (.agents/skills/meticulous-increase-coverage in FlintSH/Flare) into .claude/skills/meticulous-increase-coverage in your project. Claude Code loads it when a task matches its description.

How do I install Meticulous Increase Coverage in Codex?

Run `npx skills add FlintSH/Flare --skill meticulous-increase-coverage -a codex`. Or copy the skill folder (.agents/skills/meticulous-increase-coverage in FlintSH/Flare) into .agents/skills/meticulous-increase-coverage in your project. Codex loads it when a task matches its description.

Can I use Meticulous Increase Coverage 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 FlintSH/Flare --skill meticulous-increase-coverage -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meticulous-increase-coverage, .gemini/skills/meticulous-increase-coverage, .github/skills/meticulous-increase-coverage and .opencode/skills/meticulous-increase-coverage in your project.

What does Meticulous Increase Coverage need to run?

Going by SKILL.md and its folder, Meticulous Increase Coverage needs the command-line tools its instructions call (git).

Does Meticulous Increase Coverage 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 Meticulous Increase Coverage 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 Meticulous Increase Coverage use?

Meticulous Increase Coverage 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 Meticulous Increase Coverage use?

About 7k tokens (SKILL.md is roughly 28k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Meticulous Increase Coverage?

Skills that share tags, products or a category with Meticulous Increase Coverage: Dev-Browser CLI Automation (SawyerHood/dev-browser, 6.7k stars), Verify (WeZZard/jlens-qwen36, 402 stars), QA (blueberrycongee/termcanvas, 406 stars) and Dotnet Testing (novotnyllc/dotnet-artisan, 233 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Meticulous Increase Coverage?

FlintSH (a GitHub user) maintains it in FlintSH/Flare, which has 135 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 6, 2026.

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