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/thiientv/godmode/test-strategynpx skills add thiientv/godmode --skill test-strategygit clone --depth 1 https://github.com/thiientv/godmodeWrote 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/thiientv/godmode/test-strategy)<a href="https://agentmods.dev/skills/thiientv/godmode/test-strategy"><img src="https://agentmods.dev/badge/skills/thiientv/godmode/test-strategy.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 | $0.00079 | $0.00561 |
| Opus 5 | $0.00039 | $0.00280 |
| Sonnet 5 | $0.00016 | $0.00112 |
| Haiku 4.5 | $0.00008 | $0.00056 |
Grade A, and why
test-strategy 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 4d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Strategy
Coverage is a means; risk and failure detection are the decision criteria.
Strategy loop
- Identify critical user journeys, assets, contracts, dependencies, and recent change areas.
- Score impact and likelihood; include data loss, privacy, money, access, safety, operational, and reputation failure modes.
- Map each high-risk item to the cheapest test level that reaches the real failure: unit, contract, integration, component, browser, load, security, exploratory, or production monitoring.
- Define fixtures, environment parity, deterministic data, test ownership, test oracle, and cleanup.
- Set release gates and explicit exclusions. Include negative, boundary, retry, concurrency, migration, accessibility, and recovery paths when risk warrants them.
- Reassess after incidents, architecture changes, dependency changes, and high-churn releases.
Choose specialized test modes
- Use exploratory charters when risks or failure shapes are not understood; time-box the session, record observations, then convert repeatable discoveries into automated checks.
- Use contract tests at independently deployed consumer/provider seams; verify compatibility before deployment rather than duplicating implementation tests on both sides.
- Classify flaky tests by product race, test race, data, environment, dependency, resource contention, or selector drift. Quarantine only with an owner, evidence, expiry, and a still-visible signal; retries are not a fix.
- Use production tests only with non-destructive synthetic identities, blast-radius controls, monitoring, cleanup, and a tested abort path.
- Use agent evaluation for stochastic model-backed behavior; ordinary pass rates and snapshots do not capture variance, tool trajectory, cost, or grounding.
Read risk-matrix.md and specialized-modes.md. Avoid a universal coverage percentage, brittle snapshots with no oracle, and tests that pass only because they mock the behavior under test.
What ships with it
2 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.
- 4d ago First seen · 58 lines · 79 tokens per session scan A 9ce1c4c0094b
test-strategy is a skill published in the GitHub repository thiientv/godmode (93 stars, last pushed 8d ago), licensed MIT. It adds 79 tokens to every session and 561 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 2026-08-30.
Other skills, from other repositories
agent-evaluation-v2
Agent Evaluation workflow skill. Use this skill when the user needs Testing and benchmarking LLM agents including behavioral testing, and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
agent-evaluation
Agent Evaluation workflow skill. Use this skill when the user needs Testing and benchmarking LLM agents including behavioral testing, and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
agent-evaluation-v3
Agent Evaluation workflow skill. Use this skill when the user needs Testing and benchmarking LLM agents including behavioral testing, and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
rulesync
Generates and syncs AI rule configuration files (.cursorrules, CLAUDE.md, copilot-instructions.md) across 20+ coding tools from a single source. Use when syncing AI rules, running rulesync commands, importing or generating rule files, or managing shared AI coding configurations.
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.
loongsuite-pilot-insight
基于 LoongSuite Pilot / AI Coding Agent 日志生成事件洞察、组织洞察、数据质量、研发效能和 AI Native 使用类 SLS 报表时使用;包含 AI Coding 事件表语义,以及团队报表可选的部门维表、deptuser 组织关系、指标口径和公共 CTE,通常与 sls-dashboard-builder 一起使用。.