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 skills add BaggaT236/AI-Trading-Skills --skill skill-integration-testergit clone --depth 1 https://github.com/BaggaT236/AI-Trading-SkillsWrote 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/baggat236/ai-trading-skills/skill-integration-tester)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/skill-integration-tester"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/skill-integration-tester/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/skill-integration-tester"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/skill-integration-tester.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00058 | $0.00908 |
| Opus 5 | $0.00029 | $0.00454 |
| Sonnet 5 | $0.00012 | $0.00182 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
skill-integration-tester 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 12d 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.
This is a copy
100% identical to skill-integration-tester — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Integration Tester
Overview
Validate multi-skill workflows defined in CLAUDE.md (Daily Market Monitoring, Weekly Strategy Review, Earnings Momentum Trading, etc.) by executing each step in sequence. Check inter-skill data contracts for JSON schema compatibility between output of step N and input of step N+1, verify file naming conventions, and report broken handoffs. Supports dry-run mode with synthetic fixtures.
When to Use
- After adding or modifying a multi-skill workflow in CLAUDE.md
- After changing a skill's output format (JSON schema, file naming)
- Before releasing new skills to verify pipeline compatibility
- When debugging broken handoffs between consecutive workflow steps
- As a CI pre-check for pull requests touching skill scripts
Prerequisites
- Python 3.9+
- No API keys required
- No third-party Python packages required (uses only standard library)
Workflow
Step 1: Run Integration Validation
Execute the validation script against the project's CLAUDE.md:
python3 skills/skill-integration-tester/scripts/validate_workflows.py \
--output-dir reports/
This parses all **Workflow Name:** blocks from the Multi-Skill Workflows
section, resolves each step's display name to a skill directory, and validates
existence, contracts, and naming.
Step 2: Validate a Specific Workflow
Target a single workflow by name substring:
python3 skills/skill-integration-tester/scripts/validate_workflows.py \
--workflow "Earnings Momentum" \
--output-dir reports/
Step 3: Dry-Run with Synthetic Fixtures
Create synthetic fixture JSON files for each skill's expected output and validate contract compatibility without real data:
python3 skills/skill-integration-tester/scripts/validate_workflows.py \
--dry-run \
--output-dir reports/
Fixture files are written to reports/fixtures/ with _fixture flag set.
Step 4: Review Results
Open the generated Markdown report for a human-readable summary, or parse the JSON report for programmatic consumption. Each workflow shows:
- Step-by-step skill existence checks
- Handoff contract validation (PASS / FAIL / N/A)
- File naming convention violations
- Overall workflow status (valid / broken / warning)
What ships with it
4 files 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.
- 12d ago First seen · 131 lines · 58 tokens per session scan A ca63232cffe8
skill-integration-tester is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 8d ago), licensed MIT. It adds 58 tokens to every session and 908 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to skill-integration-tester, differing in 0 lines, and is treated as a copy.
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