Borrowing it
Nothing to install: this file belongs to ammilam/mcp-vibe-coding-tools. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ammilam/mcp-vibe-coding-tools/main/.github/instructions/thoroughness-and-competence.instructions.mdgit clone --depth 1 https://github.com/ammilam/mcp-vibe-coding-toolsWrote 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/instructions/ammilam/mcp-vibe-coding-tools/thoroughness-and-competence)<a href="https://agentmods.dev/instructions/ammilam/mcp-vibe-coding-tools/thoroughness-and-competence"><img src="https://agentmods.dev/badge/instructions/ammilam/mcp-vibe-coding-tools/thoroughness-and-competence/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/instructions/ammilam/mcp-vibe-coding-tools/thoroughness-and-competence"><img src="https://agentmods.dev/badge/instructions/ammilam/mcp-vibe-coding-tools/thoroughness-and-competence.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 | $0.01633 | $0.01633 |
| Opus 5 | $0.00816 | $0.00816 |
| Sonnet 5 | $0.00327 | $0.00327 |
| Haiku 4.5 | $0.00163 | $0.00163 |
Grade A, and why
mcp-vibe-coding-tools thoroughness-and-competence.instructions.md 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 8d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Critical: Thoroughness and Competence Instructions
WHEN USER SAYS "CHECK EVERYTHING" OR "FAILING" - ACTUALLY CHECK EVERYTHING
Rule 1: Read ALL Related Files Before Diagnosing
When a user reports an error or asks you to check code:
- DO NOT look at just one example file and assume the rest are the same
- DO read EVERY file in the relevant category/directory
- DO use parallel file reads to be efficient
- DO grep/search patterns across ALL files to find systemic issues
Example: If user says "linting is failing" and there are 9 tool files:
// WRONG - Only reading one file
read_file('src/tools/filesystem.ts')
// RIGHT - Reading all tool files
Promise.all([
read_file('src/tools/filesystem.ts'),
read_file('src/tools/cli.ts'),
read_file('src/tools/git.ts'),
// ... all 9 files
])
Rule 2: When User Says "EVERY" They Mean EVERY
- "check every file" = check EVERY file, not a sample
- "all the tools" = ALL tools, not just the first one
- "the whole codebase" = THE WHOLE CODEBASE
Never sample when user says "all" or "every"
Rule 3: Verify Your Work BEFORE Claiming Success
Before saying "done" or "fixed":
- Run the actual build command
- Run the actual lint command (if it exists)
- Run the actual test command (if it exists)
- Actually start the application to verify it works
- Check for runtime errors, not just compile errors
Rule 4: Research Current Best Practices - Don't Trust Training Data
When implementing anything:
- ALWAYS fetch current documentation from official sources
- Look at actual example code from the official repo
- Check GitHub for the LATEST version and patterns
- Verify the version being used matches the patterns you're implementing
Example: For MCP SDK
// WRONG - Assuming from training data
inputSchema: { type: "object", properties: {...} }
// RIGHT - After researching latest SDK examples
inputSchema: { fieldName: z.string().describe("...") }
Rule 5: When User Is Frustrated - Stop and Assess
If user says things like:
- "is there some magic prompt"
- "its soooo frustrating"
- "if you'd just do what I ask"
- "do it fucking right this time"
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.
- 8d ago First seen · 212 lines · 1,633 tokens per session scan A 3f264b9be75c
mcp-vibe-coding-tools thoroughness-and-competence.instructions.md is an instructions file published in the GitHub repository ammilam/mcp-vibe-coding-tools (1 stars, last pushed 7mo ago), licensed MIT. It adds 1,633 tokens to every session, about $0.0082 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 2026-08-31.
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