widescreen-research: Command for Claude Code

.claude/commands/games/mcp-dogfood.md

mcp-dogfood is a command for Claude Code from glassBead-tc/widescreen-research. It costs 0 tokens per session (1,688 once invoked), scanned A, original, MIT.

A command for testing an MCP server from inside the coding agent. It creates test scenarios, can run them, and records observations in result files.

In plain words
What is it for?
Use it to enumerate a server's capabilities, plan usage scenarios, run those scenarios, and produce a results report.
Why use it?
It provides a repeatable way to check what an MCP server actually does and document the findings.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions Claude Code.

This is glassBead-tc/widescreen-research's own configuration. It tells Claude Code how to work on widescreen-research itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything widescreen-research configures →

Reuse

Borrowing it

Nothing to install: this file belongs to glassBead-tc/widescreen-research. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/glassBead-tc/widescreen-research/main/.claude/commands/games/mcp-dogfood.md
Clone the repo
git clone --depth 1 https://github.com/glassBead-tc/widescreen-research

Made for: Claude Code.

Wrote 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.

agentmods badge for mcp-dogfood

README.md
[![agentmods](https://agentmods.dev/badge/commands/glassbead-tc/widescreen-research/mcp-dogfood/github.svg)](https://agentmods.dev/commands/glassbead-tc/widescreen-research/mcp-dogfood)
Your own site
<a href="https://agentmods.dev/commands/glassbead-tc/widescreen-research/mcp-dogfood"><img src="https://agentmods.dev/badge/commands/glassbead-tc/widescreen-research/mcp-dogfood/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.

agentmods 80×15 button for mcp-dogfood

Your own site · 80×15
<a href="https://agentmods.dev/commands/glassbead-tc/widescreen-research/mcp-dogfood"><img src="https://agentmods.dev/badge/commands/glassbead-tc/widescreen-research/mcp-dogfood.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,688 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.01688
Opus 5 $0.00000 $0.00844
Sonnet 5 $0.00000 $0.00338
Haiku 4.5 $0.00000 $0.00169

Measured 11d ago against content hash de616468c303, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

mcp-dogfood 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 11d 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.

.claude/commands/games/mcp-dogfood.md · 193 lines

How it starts

The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/mcp-dogfood

Enumerate, plan, and execute a full dogfooding pass against an MCP server from within the agent. Produces a machine-updated game state JSON and a RESULTS.md with observations and next steps.

Usage

/mcp-dogfood "$ARGUMENTS" [--run_scenarios=true] [--reasoner=sequentialthinking] [--time_window=15m]

Parameters

  • $ARGUMENTS: Target server id or connection name
  • --run_scenarios: If true, the agent will execute the planned scenarios (default: true)
  • --reasoner: Optional reasoning server to structure scenario planning (e.g., sequentialthinking, clear-thought). Default: sequentialthinking
  • --time_window: Optional time window for logs/metrics correlation

Reasoning workflow (sequentialthinking example)

When --reasoner=sequentialthinking is used, the agent plans dogfood scenarios through an explicit chain-of-thought loop using the server's sequentialthinking tool. The workflow looks like this:

  1. Initialize thinking context
  • Start with thoughtNumber = 1, an initial totalThoughts estimate (e.g., 3), and nextThoughtNeeded = true.
  1. Iterative reasoning calls
  • For each step, call the tool with:
    • thought (free-form plan/reflection content)
    • thoughtNumber, totalThoughts, nextThoughtNeeded
    • Optional flags to control structure:
      • isRevision, revisesThought to correct prior steps
      • branchFromThought, branchId to explore alternatives in parallel
      • needsMoreThoughts to signal increasing scope mid-run
  1. Read back tool output (returned as text JSON)
  • Fields include: thoughtNumber, totalThoughts, nextThoughtNeeded, branches, thoughtHistoryLength.
  • Adjust counters and decide whether to continue, revise, or branch.
  1. Convergence
  • Set nextThoughtNeeded = false when the scenario ordering and dependency plan are ready (e.g., entity-creation before dependent operations).

Example call payload (conceptual):

{
  "thought": "Enumerate capabilities; identify create→list→delete dependencies; schedule entity creation first.",
  "thoughtNumber": 1,
  "totalThoughts": 3,
  "nextThoughtNeeded": true
}

Read the full file on GitHub · 193 lines

Changes

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.

  1. 11d ago First seen · 193 lines · 0 tokens per session scan A de616468c303

Subscribe to this mod's changes

mcp-dogfood is a command published in the GitHub repository glassBead-tc/widescreen-research (6 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,688 tokens. 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.