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 terrylica/cc-skills --skill multi-agent-e2e-validationgit clone --depth 1 https://github.com/terrylica/cc-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/terrylica/cc-skills/multi-agent-e2e-validation)<a href="https://agentmods.dev/skills/terrylica/cc-skills/multi-agent-e2e-validation"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/multi-agent-e2e-validation.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector fail
SkillSpector: 2 findings, up to high
- high Privilege Escalation · line 177 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 213 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00038 | $0.02984 |
| Opus 5 | $0.00019 | $0.01492 |
| Sonnet 5 | $0.00008 | $0.00597 |
| Haiku 4.5 | $0.00004 | $0.00298 |
Grade A, and why
multi-agent-e2e-validation 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 — 412 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent E2E Validation
Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.
Overview
Prescriptive workflow for spawning parallel validation agents to comprehensively test database refactors. Successfully identified 5 critical bugs (100% system failure rate) in QuestDB migration that would have shipped in production.
When to Use This Skill
Use this skill when:
- Database refactors (e.g., v3.x file-based → v4.x QuestDB)
- Schema migrations requiring validation
- Bulk data ingestion pipeline testing
- System migrations with multiple validation layers
- Pre-release validation for database-centric systems
Key outcomes:
- Parallel agent execution for comprehensive coverage
- Structured validation reporting (VALIDATION_FINDINGS.md)
- Bug discovery with severity classification (Critical/Medium/Low)
- Release readiness assessment
Core Methodology
1. Validation Architecture (3-Layer Model)
Layer 1: Environment Setup
- Container orchestration (Colima/Docker)
- Database deployment and schema application
- Connectivity validation (ILP, PostgreSQL, HTTP ports)
- Configuration file creation and validation
Layer 2: Data Flow Validation
- Bulk ingestion testing (CloudFront → QuestDB)
- Performance benchmarking against SLOs
- Multi-month data ingestion
- Deduplication testing (re-ingestion scenarios)
- Type conversion validation (FLOAT→LONG casts)
Layer 3: Query Interface Validation
- High-level query methods (get_latest, get_range, execute_sql)
- Edge cases (limit=1, cross-month boundaries)
- Error handling (invalid symbols, dates, parameters)
- Gap detection SQL compatibility
2. Agent Orchestration Pattern
Sequential vs Parallel Execution:
Agent 1 (Environment) → [SEQUENTIAL - prerequisite]
↓
Agent 2 (Bulk Loader) → [PARALLEL with Agent 3]
Agent 3 (Query Interface) → [PARALLEL with Agent 2]
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.
- 2d ago First seen · 412 lines · 38 tokens per session scan A bec1a344aa38
multi-agent-e2e-validation is a skill published in the GitHub repository terrylica/cc-skills (62 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 2,984 once invoked, about $0.0002 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 2026-09-05.
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