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/jmagly/aiwg/auto-test-executionnpx skills add jmagly/aiwg --skill auto-test-executiongit clone --depth 1 https://github.com/jmagly/aiwgWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jmagly/aiwg/auto-test-execution)<a href="https://agentmods.dev/skills/jmagly/aiwg/auto-test-execution"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/auto-test-execution.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00023 | $0.00558 |
| Opus 5 | $0.00012 | $0.00279 |
| Sonnet 5 | $0.00005 | $0.00112 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
auto-test-execution 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 6d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
auto-test-execution
Automatically execute tests when code-generating agents write to source files, enforcing the execute-before-return pattern.
Triggers
Primary phrases matched automatically from skill description. No additional alternate expressions defined.
Purpose
This skill enforces the MetaGPT executable feedback pattern: code-generating agents must execute tests before returning results to the user. It activates automatically when agents modify source code files.
Behavior
When triggered, this skill:
-
Detect modified files:
- Track which source files the agent has written to
- Identify the relevant test framework
-
Find related tests:
- Look for test files matching the modified source
- Convention:
src/foo/bar.ts->test/unit/foo/bar.test.ts - If no tests exist, prompt agent to generate them
-
Execute tests:
- Run the project's test command focused on relevant tests
- Capture results: passed, failed, errors
-
Handle results:
- All pass: Allow agent to return results
- Failures: Trigger debug-and-retry loop (max 3 attempts)
- Persistent failures: Escalate with debug memory context
-
Update debug memory:
- Record session in
.aiwg/ralph/debug-memory/sessions/ - Extract patterns for future reference
- Record session in
Activation Conditions
activation:
always_active_for:
- software-implementer
- debugger
- test-engineer
triggered_by:
- file_write:
patterns:
- "src/**/*.ts"
- "src/**/*.js"
- "src/**/*.py"
- "**/*.go"
- "**/*.rs"
skip_when:
- test_files_only: true
- documentation_only: true
- configuration_only: true
Integration
This skill uses:
project-awareness: Detect test framework and configuration- Debug memory at
.aiwg/ralph/debug-memory/for pattern learning
References
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/rules/executable-feedback.md - Feedback rules
- @$AIWG_ROOT/agentic/code/addons/ralph/docs/executable-feedback-guide.md - Guide
- @$AIWG_ROOT/agentic/code/addons/ralph/schemas/debug-memory.yaml - Memory schema
- @.aiwg/research/findings/REF-013-metagpt.md - Research foundation
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.
- 6d ago First seen · 83 lines · 23 tokens per session scan A d85866fede1c
auto-test-execution is a skill published in the GitHub repository jmagly/aiwg (209 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 558 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
vertical-real-estate
Residential-proptech domain knowledge so architect / pm aren't naive when speccing real-estate products (listings, lead-crm, transaction-coordination, property-mgmt). Codifies MLS/IDX reality, listing status lifecycle + syndication canonical-source, long-cycle lead nurture, transaction-coordination as the high-pain…
skeptical-triage
Reusable 3-round self-challenge + arbiter pattern for filtering false positives from findings/verdicts. Use when the cost of a false-positive gate block exceeds the cost of 4 extra LLM turns.
vertical-hr-recruiting
Domain-knowledge primer for the HR & recruiting vertical (ATS, onboarding, workforce scheduling, engagement). Applied by architect/pm during spec authoring so they aren't naive about hiring pipelines, the admitted offer→onboard data-carry gap, EEO/I-9 compliance, and shift-coverage rules. Stops the four products from…
lifecycle-messaging
Email/SMS lifecycle and deliverability framework for SMB Product-Builder products that send transactional or lifecycle messages (booking reminders, CRM sequences, receipts, win-back). Codifies provider selection (Resend/Postmark/Twilio/SendGrid), domain auth (SPF/DKIM/DMARC), consent and compliance (TCPA, CAN-SPAM…
pm-planning
Decomposition methodology for pm agent — turns an approved ARCH document into a Beads task list with explicit dependencies, time-boxes, and acceptance criteria. The pipeline can only orchestrate work it can see; this skill defines what "seeable work" looks like.
well-architected
6-pillar architecture review framework. Adapted from AWS Well-Architected for use by greatcto's architect agent on every non-nano ARCH document. Forces explicit answers across operational excellence, security, reliability, performance, cost, and sustainability — not just feature design.