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 ashaykubal/essential-agents-skills --skill mock-detectiongit clone --depth 1 https://github.com/ashaykubal/essential-agents-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/ashaykubal/essential-agents-skills/mock-detection)<a href="https://agentmods.dev/skills/ashaykubal/essential-agents-skills/mock-detection"><img src="https://agentmods.dev/badge/skills/ashaykubal/essential-agents-skills/mock-detection/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/ashaykubal/essential-agents-skills/mock-detection"><img src="https://agentmods.dev/badge/skills/ashaykubal/essential-agents-skills/mock-detection.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 | $0.00013 | $0.04129 |
| Opus 5.5 | $0.00005 | $0.01652 |
| Sonnet 5.5 | $0.00003 | $0.00826 |
| Haiku 4.5 | $0.00001 | $0.00413 |
Grade A, and why
mock-detection scanned grade A with 1 finding 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 1mo 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
const mockSpawn = jest.spyOn(child_process, 'spawn') This is a copy
88% identical to mock-detection — 1,044 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 — 512 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mock Detection
Prompt template for deep mock appropriateness analysis using call graph tracing. Designed for a Sonnet sub-agent to detect T1-T4 violations and track violation scope.
When to Use This Skill
This is an internal skill loaded by the orchestrator during Test Audit pipeline.
| Context | Action |
|---|---|
/test-audit invoked |
Orchestrator loads this skill for Stage 2 |
| Test Audit pipeline triggered by hook | Orchestrator loads this skill for Stage 2 |
| Need deep mock analysis | Load directly as prompt template for Sonnet |
| Files flagged by test-classification | Analyze only needs_deep_analysis: true files |
DO NOT use for:
- Direct user invocation (not user-invocable)
- Surface-level classification (use
test-classificationskill) - Full audit synthesis (use
test-auditskill)
Role in Test Audit Pipeline
This skill provides the second stage prompt template:
test-audit (P0.8) orchestrates:
Stage 1: test-classification (Haiku) → classification YAML
Stage 2: mock-detection (Sonnet) → violations YAML ← THIS SKILL
Stage 3: synthesis (Sonnet) → audit report
The orchestrator loads this skill and constructs a 4-part prompt for a general-purpose Sonnet sub-agent.
4-Part Prompt Template
GOAL
Analyze flagged test files for T1-T4 violations using mock appropriateness rubric and call graph analysis. Track the full scope of each violation for test effectiveness calculation.
CONSTRAINTS
- Do NOT modify any files
- Only analyze files with
needs_deep_analysis: truefrom classification - Use call graph analysis to detect broken integration chains
- Track violation scope (all affected lines, not just violation line)
- Provide full context for each violation (line, snippet, reason, fix)
- Complete within 50 tool calls
CONTEXT
Classification output: {classification_yaml_path}
Files to analyze: List of files with needs_deep_analysis: true
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.
- 1mo ago First seen · 512 lines · 13 tokens per session scan A 94406ff89eb5
mock-detection is a skill published in the GitHub repository ashaykubal/essential-agents-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 4,129 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). It is 88% identical to mock-detection, differing in 1,044 lines, and is treated as a copy.
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