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Glama

standup

Reads working trees to report feature counts, blocked items, pending gates, worker liveness, and uncommitted work across tracks.

Instructions

Cross-track state in one call: counts, blocked, pending gates, worker liveness, and every worktree's uncommitted work. Reads working trees, not just commits — measured on this project, every worktree reported zero commits ahead while two held real uncommitted work, so a standup built on git history alone calls active tracks idle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoDirectory identifying the project and the tree. Defaults to this session's working directory, which in a git worktree is that worktree.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral burden. It meaningfully discloses that this tool reads working trees, not just commit history, and explains why that matters with a concrete warning about worktree divergence. It does not mention absence of side effects or performance considerations, but nothing in the description suggests mutation and the read-only tone is consistent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and efficiently front-loads the core value proposition. The second sentence uses an anecdote to justify the working-tree read behavior, which is useful albeit slightly verbose; it still earns its place by alerting the agent to a subtle correctness pitfall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has only one optional, schema-documented parameter, and the description enumerates the key output dimensions even though no output schema exists. It doesn't detail return formatting or exact field names, but for a cross-track status snapshot the described scope is sufficient for a capable agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the single 'cwd' parameter is already well documented in the schema. The tool description does not add parameter-level detail, but because the schema fully covers it, the baseline rating of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete deliverable: cross-track state in one call, and enumerates exactly what it surfaces: counts, blocked items, pending gates, worker liveness, and uncommitted worktree changes. It clearly differentiates from sibling tools like feature_list, gate_list, and worker_list by being an aggregate cross-track snapshot rather than a single-track listing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It establishes clear usage context: use this when you want cross-track state in a single call. It does not explicitly name alternatives or exclusion conditions, but the description's emphasis on reading working trees and covering multiple tracks gives an agent enough context to choose it over narrower sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.