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.
npx agentmods add skills/evolplus/talos/qa-execution-runnernpx skills add evolplus/talos --skill qa-execution-runnergit clone --depth 1 https://github.com/evolplus/talosWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00080 | $0.01951 |
| Opus 5 | $0.00040 | $0.00975 |
| Sonnet 5 | $0.00016 | $0.00390 |
| Haiku 4.5 | $0.00008 | $0.00195 |
Grade A, and why
qa-execution-runner 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.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Execution Runner
Use
Use this skill for every QA-Exec dispatch.
Inputs
- Target task file and linked US/FRs
docs/test-cases/by-us/<US-ID>/anddocs/test-cases/by-task/<task-id>/- Executable specs named by each TC
docs/deploy-reports/<task-id>.md- SRS §3.4.6 Environment Configuration when the project has FE/BE runtime scope
- UI artifacts: design refs, visual specs, instrumentation contract, UI refs
Procedure
- Gather test cases:
- read linked US IDs and FR IDs from the task;
- load every linked by-us functional TC;
- load task-scoped structural/api/e2e/functional TCs;
- halt on missing expected coverage.
- For UI tasks, enforce strict artifact presence:
- by-task TC directory with at least one TC;
docs/uiux/visual-specs/<task-id>.md;- instrumentation contract when UI selectors/testIDs are expected.
- Run bidirectional instrumentation coverage for UI tasks:
- every contract-declared testID appears in at least one spec;
- when bundle is reachable, every contract-declared testID ships in the bundle.
- Route spec gaps to QA-Author and bundle gaps to FE Dev.
- Pre-run checks:
- parse deploy report
## Test Environment; - verify base URLs, fixtures, env vars, build/commit/instrumentation identity;
- verify
env_files,env_templates, andenv_validationare present;compose_config_quietispass;missing_required_envisnone;srs_environment_contractispass;declared_config_keys_statusisall documented; andsecret_values_redactedistrue; - when SRS §3.4.6 declares runtime keys, verify the deploy report lists each declared key name with a non-secret status summary only; missing declared keys are a blocked environment state routed back to DevOps;
- verify every
Executable:file exists; - grep executable specs for
TODO: instrumentation-contract; any hit isblocked. - inspect fixture reset behavior: direct DB INSERT/TRUNCATE must be followed by a synchronous reset/flush of
affected caches and process-global runtime state before the SUT is read; missing capability is
blocked: test-harness-state-resetrouted to BE Dev. - for direct-DB fixtures, require deploy-report
test_endpoints_enabled: trueandruntime_state_reset.synchronous_probe: passplusruntime_state_reset.behavioral_fresh_read_probe: pass; missing or failed evidence routes to DevOps/BE Dev and blocks the runner. - inspect runner concurrency: any global DB reset, global cache flush, or process-global reset requires per-worker
isolation or a dedicated one-worker project; otherwise mark
blocked: shared-test-state. - compare navigation assertions with the signed-off URL/canonicalization contract. A path-only
$assertion that rejects required query parameters isblocked: test-spec-contract-drift, routed to QA-Author. - if any pre-run check is blocked, halt before invoking the runner. Record the blocked reason and owning role; do not continue to Step 7 with a known-invalid harness/spec.
- parse deploy report
- Skip deprecated US test cases with reason
deprecated-us; report the skip. - Select runner from
solution-defaults, project ADRs, and SRS UI Introspection Profile. Loadui-test-executionand any relevant runner reference. - Invoke the runner against the deployed environment, never against production data.
- For UI tasks:
- Tier 1 functional always;
- Tier 2 structural/token always where introspection allows;
- Tier 3 visual diff only when SRS marks Visual-Critical.
- Validate visual spec before UI execution:
Status: Generated;- Figma version matches confirmed task version;
- handoff hash matches current handoff.
- reference-render Node IDs, Figma version, dimensions, and checksums are present;
- Visual Composition Assertions and Asset Assertions are non-empty and cover every handoff composition/AST row.
- Report each TC as
pass,fail,blocked, orskipped. - For failures, attach actual vs expected, logs/screenshots/traces/diffs, and suspected track.
- Write
docs/qa-reports/<task-id>.mdand artifacts underdocs/qa-reports/<task-id>/. - Emit
plan-update.json:in-test -> doneonly when no fail/blocked cases remain; otherwisein-test -> failed.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 143 lines · 80 tokens per session scan A 45b45c01d221
qa-execution-runner is a skill published in the GitHub repository evolplus/talos (8 stars, last pushed 28d ago), licensed Apache-2.0. It adds 80 tokens to every session and 1,951 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.