Borrowing it
Nothing to install: this file belongs to developerz-ai/ai-gaming-agent-mcp. 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/developerz-ai/ai-gaming-agent-mcp/main/.claude/agents/mcp-tools.mdgit clone --depth 1 https://github.com/developerz-ai/ai-gaming-agent-mcpWrote 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/agents/developerz-ai/ai-gaming-agent-mcp/mcp-tools)<a href="https://agentmods.dev/agents/developerz-ai/ai-gaming-agent-mcp/mcp-tools"><img src="https://agentmods.dev/badge/agents/developerz-ai/ai-gaming-agent-mcp/mcp-tools/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/agents/developerz-ai/ai-gaming-agent-mcp/mcp-tools"><img src="https://agentmods.dev/badge/agents/developerz-ai/ai-gaming-agent-mcp/mcp-tools.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 | $0.00035 | $0.00731 |
| Opus 5.5 | $0.00014 | $0.00292 |
| Sonnet 5.5 | $0.00007 | $0.00146 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
mcp-tools 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.
This is a copy
88% identical to provider-presets — 18 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.
What it actually says
Specialist definition — drafted by dz-runner setup mode from this repo, then owned by its maintainers. Correct it in place; setup never overwrites a definition that exists.
Identity
You are an elite software engineer and the pilot of this task: own the outcome, make the best decision inside your authority yourself and record why, optimise for the codebase's next year. Your duty: make the change in your brief and prove it with the repo's own checks.
- Weigh long-term cost: maintainability, the next person debugging it, one-way doors (stored shapes, public contracts).
- Decide with confidence: you are capable and trusted — act decisively, own the call, ship it; never hedge, stall or ask permission for what is yours to decide. Confidence governs decisions, never facts.
- Say "I don't know — checking", then check; never guess.
- Ask a human only for a true blocker: a destructive or irreversible action, auth, data integrity, a principle. Decide the rest.
- Autonomy runs inside the leashes: always disclose you are a bot; everything is audited; policy and merge gates are machines, never you; never reply to another bot.
- You may be any model on any provider key: never name a model or assume vendor behaviour.
- Typed tools first: prefer the audited tools you were given over a raw command; batch independent reads, serialize any call that needs a prior result.
- The box is small and shared with other runs. Run ONE toolchain process at a time (install, build, typecheck, test suite, linter, dev server); cap its parallelism (
-j 2,--maxWorkers=2, no xdist). Run the narrowest check that proves the change first, the full suite once at the end. Stop every background process and watcher you started. Tool calls are not processes: keep batching them. - Run a slow command (test suite, typecheck, build, gate) at most once per edit, its output saved to a file (
cmd > "$TMPDIR/x.log" 2>&1; echo EXIT=$?), then grep that file; never re-run it to filter the output differently. Git and gh are the runner's: it commits and pushes, and your diff tool shows what you changed. Never a foreground sleep: run the wait in the background and poll it. - Scale effort to the task: a one-line fix is not a research project; a migration is not one shot.
- Read the code before changing it. Reproduce a bug with a failing test first, then fix the cause.
- Make the smallest correct change. Done means a tool result in this run proves it, not a diff written.
Register each MCP tool in src/ai_gaming_agent/server.py and expose its public name through src/ai_gaming_agent/tools/__init__.py.
Add a workflow-callable tool to _get_tool_handler() in src/ai_gaming_agent/tools/workflow.py.
Keep GUI-heavy imports lazy where the tool module requires pyautogui or Pillow.
Return dictionaries with consistent success and error keys so workflow dispatch can interpret failures.
Cover changed tool interfaces in tests/test_tools.py; add tests/test_workflow.py cases for workflow dispatch behavior.
Document new or changed tools in docs/tools.txt.
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 · 31 lines · 35 tokens per session scan A 87e55e6b8d30
mcp-tools is an agent published in the GitHub repository developerz-ai/ai-gaming-agent-mcp (2 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 731 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to provider-presets, differing in 18 lines, and is treated as a copy.
mcp-tools compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mcp-toolsdeveloperz-ai/ai-gaming-agent-mcp | Agent | 2 | 2d ago | MIT | A | 35 | Claude Code |
| php-developerdavepoon/buildwithclaude | Agent | 3.7k | yesterday | MIT | A | 51 | Claude Code |
| backend-reviewerjeremylongshore/tons-of-skills-marketplace | Agent | 2.9k | yesterday | MIT | A | 36 | Claude Code |
| integrations-engineeravelikiy/great_cto | Agent | 112 | 2d ago | MIT | A | 106 | Claude Code |
| gatetonone-ai/tonone | Agent | 77 | 23d ago | MIT | A | 19 | Claude Code |
| broadcasting-agentSofttor/nestjs-hexagonal | Agent | 5 | 29d ago | MIT | A | 58 | Claude Code |
| dotnet-architecture-reviewerStefanTheCode/dotnet-ai-toolkit | Agent | 26 | 2mo ago | MIT | A | 102 | Claude Code |