Agent skill

Eng Real Scenario QA

by compozy in compozy/compozy

Dogfoods Compozy through an autonomous startup scenario with live providers, cross-surface observation, and strict evidence audit.

MITAuto-check passedTesting & QA

Install Eng Real Scenario QA

skills CLI
$ npx skills add compozy/compozy --skill eng-real-scenario-qa -a claude-code

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

GitHub CLI
$ gh skill install compozy/compozy eng-real-scenario-qa --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/compozy/compozy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/eng/eng-real-scenario-qa .claude/skills/eng-real-scenario-qa && 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
eng-real-scenario-qa
GitHub stars
2.8k
Token cost
~3.4k tokens
SKILL.md length
1,636 words
Files
21 (incl. scripts, references, assets)
Skills in repo
47
Repo updated
First seen
Licence
MIT

At a glance

Dogfoods Compozy through an autonomous startup scenario with live providers, cross-surface observation, and strict evidence audit.

  • Works in 3 steps: Read… → Resolve the playbook ref → Record PLAYBOOK_REF.
  • Complex-integration QA
  • SKILL.md covers Required Inputs, Procedures and Error Handling
  • Runs Python and Shell scripts from its folder; calls python3

What it does

Eng Real Scenario QA is an agent skill from compozy/compozy. Dogfoods Compozy through an autonomous startup scenario with live providers, cross-surface observation, and strict evidence audit. Use for release or complex-integration QA. Do not use for smoke, static, mock-only, or unit-test work.

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 24 other files, including scripts, reference files and assets (for example `assets/operator-kickoff-template.md`, `references/charter.schema.json` and `references/forbidden-prompt-phrases.md`).

It sits in Testing & QA, covering Unit testing. The repository describes itself as: An operating system for AI agents. Plug in the agent CLIs you already use (Claude Code, Codex, Gemini CLI, Cursor) and they become a team: they split the work, hand tasks to each… The licence is MIT.

When your agent uses it

  • Complex-integration QA
  • Tasks that involve Unit testing

Example prompts

  • “Use the eng-real-scenario-qa skill to dogfood Compozy through an autonomous startup scenario with live providers, cross-surface observation, and…”
  • “/eng-real-scenario-qa”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Read .agents/skills/eng/eng-real-scenario-qa/references/playbook-catalog.md in full.
  2. Resolve the playbook ref
  3. Record PLAYBOOK_REF.

What it can do on your machine

Read from SKILL.md and the folder at commit c15729c. 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 7 files in scripts/ (Python and Shell, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

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

  • Network

    No URLs in SKILL.md.

    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

Eng Real Scenario QA loads about 3.4k tokens when it runs, and up to ~20k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 1,636 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~20k

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 compozy/compozy at commit c15729c, republished under its MIT licence (© compozy). 1,636 words, ~3,405 tokens.

Download SKILL.mdSave it as .claude/skills/eng-real-scenario-qa/SKILL.md (or your agent's skills folder). This skill also uses 20 other files; get the full folder from GitHub.
name
eng-real-scenario-qa
description
Dogfoods Compozy through an autonomous startup scenario with live providers, cross-surface observation, and strict evidence audit. Use for release or complex-integration QA. Do not use for smoke, static, mock-only, or unit-test work.
trigger
explicit
argument-hint
[playbook-ref]

Real Scenario QA

Execute release-grade QA by running an entire fictional startup project on the Compozy runtime and observing the result. The runtime drives the work; the observer never tells agents they are being evaluated. The auditor enforces real deliverables (compiled/parsed/runnable artifacts) and real collaboration (review cycles, disagreement resolution).

The skill rejects any prompt that frames the work as QA. See references/forbidden-prompt-phrases.md.

Required Inputs

  • playbook-ref (optional): Slug of the playbook to run (e.g., northstar-pay, devtool-oss-launch, consumer-saas-growth). When omitted, rotate from the previous run's PLAYBOOK_REF recorded in bootstrap-manifest.json.

Procedures

Step 1: Select the Playbook

  1. Read .agents/skills/eng/eng-real-scenario-qa/references/playbook-catalog.md in full.
  2. Resolve the playbook ref:
    • If the user supplied a slug, validate it exists at references/playbooks/<slug>.md.
    • Otherwise, list references/playbooks/*.md (excluding README) and rotate from the previous PLAYBOOK_REF.
  3. Record PLAYBOOK_REF.

Done when: one valid playbook is selected and differs from the previous run when rotation applies.

Step 2: Bootstrap the Lab With the Playbook

  1. Activate eng-qa-bootstrap with scenario $PLAYBOOK_REF and --playbook "$PLAYBOOK_REF"; follow its setup, handoff, and continuation contract (Steps 1–4). Keep the lab alive for execution; bootstrap Step 5 runs at this workflow's terminal teardown.
  2. Consume the canonical BOOTSTRAP_MANIFEST and its emitted paths. Never reconstruct provider, browser, proxy, audit, or teardown state here.
  3. Confirm the selected playbook, agent registrations, open-task tree, required deliverables/collaboration, and populated charter all belong to the same healthy manifest. Register only RUNTIME_WORKSPACE_PATH with Compozy, and capture the returned public id as RUNTIME_WORKSPACE_ID; agents must not see the lab's qa-artifacts/ or audit contracts.

Done when: bootstrap's setup/handoff criteria pass, the lab is alive, and the charter has no placeholders.

Step 3: Activate Companion Skills

  1. Use qa-report with qa-docs-path=docs/qa to plan the playbook-product validation as session charters (persona + journey + tour + time-box on the playbook deliverables — never on QA itself). QA_OUTPUT_PATH remains the lab-side scratch root (journey log, observation, kickoff evidence); the living QA state lives in the repo's docs/qa/.
  2. Use qa-execution with qa-docs-path=docs/qa to run those sessions against the lab (does the TSX page render? do scripts run? does the canary control respond?), driving the lab's base URL/daemon from the bootstrap env block.
  3. Reuse bootstrap's existing isolation envelope, including during concurrent work. eng-worktree-isolation allocates non-bootstrap runs; do not allocate a second home over this manifest.
  4. Use debugging guidance when the cause is unclear or fixes have failed; use no-workarounds when a proposed fix suppresses a symptom. A known, direct repair does not require both skills.
  5. Apply provider-home, Web-proxy, config-write, PID-registration, and teardown policy directly from the bootstrap manifest.

Done when: the living QA plan and execution use one bootstrapped manifest and no second isolation envelope is allocated.

Step 4: Post the Operator Kickoff

  1. After runtime agents, sessions, and the deterministic task ids from .compozy/tasks/open-tasks.json exist under the shared RUNTIME_WORKSPACE_PATH, prepare task activation behind a scheduler barrier (mutating): python3 .agents/skills/eng/eng-real-scenario-qa/scripts/activate-playbook-tasks.py prepare --workspace "$WORKSPACE_PATH" --qa-output-path "$QA_OUTPUT_PATH" --manifest "$BOOTSTRAP_MANIFEST" --compozy-bin "${COMPOZY_BIN:-compozy}"
  2. Render and validate the kickoff payload (mutating only the inspectable payload file): python3 .agents/skills/eng/eng-real-scenario-qa/scripts/post-operator-kickoff.py --workspace "$WORKSPACE_PATH" --playbook "$PLAYBOOK_REF" --qa-output-path "$QA_OUTPUT_PATH" --manifest "$BOOTSTRAP_MANIFEST"
  3. The helper aborts with exit code 2 if the rendered kickoff contains any phrase from references/forbidden-prompt-phrases.md. Rewrite the playbook's kickoff_brief when blocked.
  4. Read <WORKSPACE_PATH>/.compozy/operator-kickoff.txt. Deliver that text verbatim once and capture the provider stream: compozy session prompt <operator-session-id> "$(cat $WORKSPACE_PATH/.compozy/operator-kickoff.txt)" -o jsonl > $QA_OUTPUT_PATH/qa/operator-kickoff.jsonl
  5. Confirm the successful post from its non-empty evidence (mutating), then release the queued task runs (mutating): python3 .agents/skills/eng/eng-real-scenario-qa/scripts/post-operator-kickoff.py --workspace "$WORKSPACE_PATH" --playbook "$PLAYBOOK_REF" --qa-output-path "$QA_OUTPUT_PATH" --manifest "$BOOTSTRAP_MANIFEST" --confirm-posted "$QA_OUTPUT_PATH/qa/operator-kickoff.jsonl" python3 .agents/skills/eng/eng-real-scenario-qa/scripts/activate-playbook-tasks.py release --workspace "$WORKSPACE_PATH" --qa-output-path "$QA_OUTPUT_PATH" --manifest "$BOOTSTRAP_MANIFEST" --kickoff-evidence "$QA_OUTPUT_PATH/qa/operator-kickoff.jsonl" --compozy-bin "${COMPOZY_BIN:-compozy}"
  6. Confirm the manifest reports KICKOFF_POSTED=true, KICKOFF_TIMESTAMP is set, task activation is released, and the scheduler is unpaused. Send no further prompt to any agent under test; a stall becomes a bug.

Done when: every declared task has one queued run behind the barrier, exactly one evidenced kickoff is confirmed, dispatch is released, and the observer has no path for a second agent prompt.

Step 5: Observe the Runtime

  1. Run the observer (read-only) for the configured window: python3 .agents/skills/eng/eng-real-scenario-qa/scripts/observe-runtime.py --scenario-workspace "$WORKSPACE_PATH" --runtime-workspace "$RUNTIME_WORKSPACE_PATH" --workspace-id "$RUNTIME_WORKSPACE_ID" --api-base-url "$COMPOZY_WEB_API_PROXY_TARGET" --compozy-home "$COMPOZY_HOME" --compozy-bin "${COMPOZY_BIN:-compozy}" --qa-output-path "$QA_OUTPUT_PATH" --duration-sec 1800 --stall-threshold-sec 300
  2. Before polling, the observer requires workspace info "$RUNTIME_WORKSPACE_ID" to resolve to RUNTIME_WORKSPACE_PATH. It then derives progress only from public Task catalog/detail, Loop runs, loop why, and loop events reads. It records only durable state transitions in observation-summary.json; journey-log.jsonl remains supporting evidence and never controls the stall clock.
  3. While the observer polls, capture cross-surface evidence without directing agents:
    • CLI: independently capture compozy task list --workspace "$RUNTIME_WORKSPACE_ID" -o json, plus agent and session lists against the same isolated COMPOZY_HOME.
    • API: read endpoints that intersect the playbook's primary domain.
    • Web: open the Compozy web app via browser-use:browser (or the agent-browser fallback) against $COMPOZY_WEB_API_PROXY_TARGET. Capture DOM snapshot, URL, screenshot.
    • Runtime: compare the independent Task catalog capture with the observer's Task account for the same window.
  4. Record observer-only or out-of-band supporting evidence with the mutating helper .agents/skills/eng/eng-real-scenario-qa/scripts/record-scenario-action.py; those rows never count as runtime progress.
  5. On exit 1, open <QA_OUTPUT_PATH>/qa/observation-summary.json, identify the unchanged active Tasks or Loop runs, and proceed to Step 6 without prompting an agent. On exit 2, record the exact public-read error; a malformed or failed read is not a stall or a pass.
  6. On exit 0, require the observer account and independent Task catalog capture to agree before proceeding to Step 6.

Done when: the observation window, terminal state, explicit stall, or honest read error completes with indexed CLI, API, Web, runtime, and provider evidence; the independent catalog comparison is recorded; and no observer prompt follows kickoff.

Step 6: Audit, Diagnose, Fix, Re-Verify

  1. Maintain the dated report at docs/qa/reports/<YYYY-MM-DD>-<playbook-ref>.md through qa-report/qa-execution; index lab-side evidence by path rather than copying it into the repository.
  2. Diagnose and fix real runtime defects, using the relevant companion only for an unresolved concern; fix playbook authoring defects in the playbook source and restart from Step 2.
  3. After the last relevant code change, satisfy the enclosing workstream's root gate policy and cite its current evidence. A QA-only run reuses unchanged gate evidence; PR CI applies when delivering a PR.
  4. Run the mutating strict auditor last, passing the durable report explicitly: python3 .agents/skills/eng/eng-real-scenario-qa/scripts/audit-qa-evidence.py --qa-output-path "$QA_OUTPUT_PATH" --final-report "docs/qa/reports/<YYYY-MM-DD>-<playbook-ref>.md" --strict
  5. Auditor exit code 2 is a blocking failure. Read qa-audit-report.json and act per check. All durable bugs go to the repo's global registry as docs/qa/bugs/BUG-<YYYYMMDD>-<slug>.md (dedup against the registry first, per qa-report's bug-registry rules) and are linked into the affected docs/qa/scenarios/*.md files:
    • C15 forbidden phrase in a prompt → rewrite the playbook source (system_prompt or kickoff_brief), not the auditor or the regex list.
    • C16 deliverable count short → file a runtime bug (which Compozy agent failed to produce the artifact, why, what state shows the failure). Do not author the missing artifact yourself — the runtime is what's under test.
    • C17 collaboration loop short → file a runtime bug describing which agent or review cycle did not complete. Cite journey-log timestamps.
    • C18 stall → the registry bug is mandatory and must name the silent agent and stalled task.
  6. After a fix, rerun affected checks and the failed journey, then refresh invalidated gate/audit evidence. Unchanged passing evidence remains valid; a final PASS still requires the strict auditor to accept the resulting execution. Observer changes use the read-only verification helper: python3 .agents/skills/eng/eng-real-scenario-qa/scripts/test_observe_runtime.py.
  7. Update affected scenario verdicts and append the bootstrap continuation block only when the same active loop will continue.
Show full SKILL.md (406 more words)Show less

Done when: the dated report, fresh local gate, scenario verdicts, strict audit, and indexed evidence all describe the same execution with no blocker.

Step 7: Tear Down the Lab (MANDATORY)

  1. Complete eng-qa-bootstrap Step 5 using the current manifest's exact TEARDOWN_COMMAND. This applies on every terminal verdict — PASS, FAIL, BLOCKED, or abort.
  2. Cite <QA_OUTPUT_PATH>/qa/teardown.json ("clean": true) in the final summary. Survivors (exit 1) are a blocking failure.
  3. Only exception: an explicitly continuing timed loop keeps the lab alive; the continuation that ends the loop inherits the teardown obligation. A stalled or aborted run tears down like any other — the stall evidence lives in files, not in live processes.

Done when: the current lab's teardown.json reports "clean": true and no owned process survives.

Error Handling

  • If bootstrap fails to load the playbook, validate the playbook against .agents/skills/eng/eng-real-scenario-qa/references/playbook-schema.json; a real-scenario run never falls back to a generic charter.
  • If the kickoff helper aborts on a forbidden phrase, rewrite the playbook's kickoff_brief. Do not edit references/forbidden-prompt-phrases.md to remove the rule.
  • If task activation preparation fails, keep the owned scheduler barrier paused, inspect qa/task-activation.json, and retry with the same idempotency keys. Never post the kickoff with a partial task tree.
  • If kickoff delivery or confirmation fails, keep dispatch paused. Retry only the same unconfirmed delivery when no provider evidence exists; once evidence exists, confirmation is the only valid next step. Release refuses an empty kickoff transcript or an unconfirmed manifest.
  • If observe-runtime.py reports a stall, preserve the unchanged public snapshot and file the runtime stall without injecting a prompt. If it reports exit 2, diagnose the named public read instead of relabeling the error as a stall.
  • If a required deliverable type cannot be parsed by the auditor (e.g., a TSX file with non-standard exports), diagnose whether the artifact violates the playbook contract or the auditor cannot handle valid output. Record the owning defect and repair its source for a new run; never re-prompt an agent under test after kickoff or author its missing deliverable.
  • If browser-use:browser is unavailable, follow the agent-browser fallback per the bootstrap browser policy. Do not silently drop the Web surface.
  • If providers are unreachable, record the boundary in provider-attempt.json. The run verdict becomes BLOCKED, never PASS.
  • If the auditor's playbook_compliance block reports zero counts despite agents working, confirm WORKSPACE_PATH/.compozy/playbook.json exists and journey-log.jsonl is being written. Empty counts often mean the runtime is not wired to the journey log — that is a runtime bug.

© compozy, 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 20 other files (scripts, references, assets) in .agents/skills/eng/eng-real-scenario-qa of compozy/compozy.

  • SKILL.md
  • assets/operator-kickoff-template.md
  • references/charter.schema.json
  • references/forbidden-prompt-phrases.md
  • references/playbook-catalog.md
  • references/playbook-schema.json
  • references/playbooks/consumer-saas-growth.md
  • references/playbooks/devtool-oss-launch.md
  • references/playbooks/northstar-pay.md
  • references/scenario-contract.schema.json
  • scripts/activate-playbook-tasks.py
  • scripts/audit-qa-evidence.py
  • scripts/init-scenario-workspace.sh
  • scripts/observe-runtime.py
  • scripts/playbook_loader.py
  • scripts/post-operator-kickoff.py
  • scripts/record-scenario-action.py
  • … and 4 more

Open the folder on GitHubat commit c15729c

Compare with similar skills

Eng Real Scenario QA 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.

Eng Real Scenario QA compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Eng Real Scenario QA this skillcompozy/compozy2.8k—~3.4kAutomated safety check: PassMIT
TDD WorkflowhellangleZ/burn-in-cceverywhere-ralph11211 repos~2.4kAutomated safety check: PassNone
Testing OpenLogi UIAprilNEA/OpenLogi23k—~1.1kAutomated safety check: PassApache-2.0
Go Testingcxuu/golang-skills1721 repos~1.3kAutomated safety check: PassApache-2.0
Contractssamchon/nestia2.2k—~1.3kAutomated safety check: PassMIT
Cohesion Over TestabilityEpicenterHQ/epicenter4.8k—~2kAutomated safety check: PassCustom licence

Similar skills

  • TDD Workflow

    hellangleZ/burn-in-cceverywhere-ralph

    A skill your agent uses when writing new features, fixing bugs, or refactoring code.

    112 GitHub starsUsed in 11 repos~2.4k tokens
    Testing & QAAuto-check passed
  • Testing OpenLogi UI

    AprilNEA/OpenLogi

    Verifies OpenLogi's native GPUI interface with focused tests, the component gallery and a mock agent, choosing the evidence that fits each change.

    23k GitHub stars~1.1k tokensUpdated today
    Testing & QAAuto-check passed
  • Go Testing

    cxuu/golang-skills

    A skill your agent uses when writing, reviewing, or improving Go test code — including table-driven tests, subtests, parallel tests, test helpers, test doubles, and assertions with cmp.Diff.

    172 GitHub starsUsed in 1 repo~1.3k tokens
    Testing & QAAuto-check passed
  • Contracts

    samchon/nestia

    Defines self-acknowledgments for production declarations and tests.

    2.2k GitHub stars~1.3k tokensUpdated 2 days ago
    Testing & QAAuto-check passed
  • Cohesion Over Testability

    EpicenterHQ/epicenter

    Collapse test-shaped production boundaries while preserving behavior and coverage.

    4.8k GitHub stars~2k tokensUpdated yesterday
    Testing & QAAuto-check passed
  • JS-in-HTML Testing

    liaohch3/claude-tap

    Tests JavaScript embedded in an HTML file in two layers: pytest checks of the logic ported to Python, and Playwright runs in a real browser for the DOM.

    3.3k GitHub stars~924 tokensUpdated 17 days ago
    Testing & QAAuto-check passed

More from compozy/compozy

All 47 skills in this repo
  • Eng Test Conventions

    compozy/compozy

    Go test-shape discipline for Compozy. An agent skill from compozy/compozy.

    2.8k GitHub stars~467 tokensUpdated yesterday
    Auto-check passed
  • Assistant UI

    compozy/compozy

    Guide for assistant-ui library - AI chat UI components. An agent skill from compozy/compozy.

    2.8k GitHub stars~958 tokensUpdated yesterday
    Auto-check passed
  • Guide for assistant-ui UI primitives - ThreadPrimitive, ComposerPrimitive, MessagePrimitive.

    2.8k GitHub stars~999 tokensUpdated yesterday
    Auto-check passed
  • Assistant UI Runtime

    compozy/compozy

    Guide for assistant-ui runtime system and state management. An agent skill from compozy/compozy.

    2.8k GitHub stars~856 tokensUpdated yesterday
    Auto-check passed
  • Assistant UI Streaming

    compozy/compozy

    Guide for assistant-stream package and streaming protocols. An agent skill from compozy/compozy.

    2.8k GitHub stars~813 tokensUpdated yesterday
    Auto-check passed
  • Assistant UI Tools

    compozy/compozy

    Guide for tool registration and tool UI in assistant-ui. An agent skill from compozy/compozy.

    2.8k GitHub stars~868 tokensUpdated yesterday
    Auto-check passed

Categories

Questions about Eng Real Scenario QA

What does Eng Real Scenario QA do?

Dogfoods Compozy through an autonomous startup scenario with live providers, cross-surface observation, and strict evidence audit. Eng Real Scenario QA is an agent skill from compozy/compozy. Dogfoods Compozy through an autonomous startup scenario with live providers, cross-surface observation, and strict evidence audit.

When should I use Eng Real Scenario QA?

Eng Real Scenario QA fits situations like: complex-integration QA; tasks that involve Unit testing.

How do I install Eng Real Scenario QA in Claude Code?

Run `npx skills add compozy/compozy --skill eng-real-scenario-qa -a claude-code`. Or copy the skill folder (.agents/skills/eng/eng-real-scenario-qa in compozy/compozy) into .claude/skills/eng-real-scenario-qa in your project. Claude Code loads it when a task matches its description.

How do I install Eng Real Scenario QA in Codex?

Run `npx skills add compozy/compozy --skill eng-real-scenario-qa -a codex`. Or copy the skill folder (.agents/skills/eng/eng-real-scenario-qa in compozy/compozy) into .agents/skills/eng-real-scenario-qa in your project. Codex loads it when a task matches its description.

Can I use Eng Real Scenario QA 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 compozy/compozy --skill eng-real-scenario-qa -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/eng-real-scenario-qa, .gemini/skills/eng-real-scenario-qa, .github/skills/eng-real-scenario-qa and .opencode/skills/eng-real-scenario-qa in your project.

What does Eng Real Scenario QA need to run?

Going by SKILL.md and its folder, Eng Real Scenario QA needs Python and a shell for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3; A Bash shell.

Does Eng Real Scenario QA access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Eng Real Scenario QA 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 Eng Real Scenario QA use?

Eng Real Scenario QA 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 Eng Real Scenario QA use?

About 3.4k tokens (SKILL.md is roughly 14k 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 17k tokens, read only when the agent opens those files.

What are the alternatives to Eng Real Scenario QA?

Skills that share tags, products or a category with Eng Real Scenario QA: TDD Workflow (hellangleZ/burn-in-cceverywhere-ralph, 112 stars), Testing OpenLogi UI (AprilNEA/OpenLogi, 23k stars), Go Testing (cxuu/golang-skills, 172 stars) and Contracts (samchon/nestia, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Eng Real Scenario QA?

compozy (a GitHub organization) maintains it in compozy/compozy, which has 2,791 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on October 8, 2026.

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