Borrowing it
Nothing to install: this file belongs to sebazai/faceit-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/sebazai/faceit-mcp/main/.cursor/commands/regenerate-tools.mdgit clone --depth 1 https://github.com/sebazai/faceit-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/commands/sebazai/faceit-mcp/regenerate-tools)<a href="https://agentmods.dev/commands/sebazai/faceit-mcp/regenerate-tools"><img src="https://agentmods.dev/badge/commands/sebazai/faceit-mcp/regenerate-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/commands/sebazai/faceit-mcp/regenerate-tools"><img src="https://agentmods.dev/badge/commands/sebazai/faceit-mcp/regenerate-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 | $0.00000 | $0.00345 |
| Opus 5 | $0.00000 | $0.00172 |
| Sonnet 5 | $0.00000 | $0.00069 |
| Haiku 4.5 | $0.00000 | $0.00034 |
Grade A, and why
regenerate-tools 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://open.faceit.com/data/v4/docs/swagger.json -o swagger.json What it actually says
/regenerate-tools
Regenerate the FACEIT MCP tool modules from swagger.json and verify the
server still assembles.
When this command is invoked, do the following in order:
-
Fetch the latest
swagger.jsonfrom the FACEIT Data API and save it to the repo root (it is gitignored by design):curl -fsSL https://open.faceit.com/data/v4/docs/swagger.json -o swagger.jsonIf the download fails, stop and report the error to the user.
-
If the user asked for description improvements or renames, edit
scripts/generate_tools.py— specificallyTAG_HINTSfor disambiguation hints andOPERATION_OVERRIDESfor renames. Never hand-edit files undersrc/faceit_mcp/tools/. -
Run the generator:
python scripts/generate_tools.pyExpect output ending with
Generated 64 tools across 13 modules.If the count changes, mention it explicitly to the user. -
Run the smoke test:
FACEIT_API_KEY=placeholder python -c " import asyncio from faceit_mcp.server import mcp tools = asyncio.run(mcp.list_tools()) print(len(tools)) "The output must be
64(or the new expected count). -
Summarise the diff under
src/faceit_mcp/tools/— which tool descriptions changed and why. Do not commit unless the user asked you to.
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 · 43 lines · 0 tokens per session scan A 3abe549de85f
regenerate-tools is a command published in the GitHub repository sebazai/faceit-mcp (0 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 345 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.