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Glama

Install a reviewed plan

open77_workshop_install
Destructive

Installs human-approved plans after verifying explicit consent and the plan's exact hash, then returns a job id for follow-up.

Instructions

Installs a plan the human has read and accepted. Requires consent=true and the plan's sha256 exactly as open77_workshop_plan returned it; Warden refuses anything else. Returns the job id; follow it with open77_workshop_job. Never call this without the human's explicit yes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planIdYes
sha256Yes
consentYesThe human explicitly accepted this plan

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations, it discloses strict validation behavior ('Warden refuses anything else'), the necessity of exact sha256 matching, and the return value (job id). This gives the agent the behavioral context needed to invoke and monitor the operation correctly.

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

Conciseness5/5

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

Four short sentences, each adding a distinct piece of information: purpose, prerequisites, return value/next step, and a safety constraint. Nothing is wasted and the key action is front-loaded.

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

Completeness5/5

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

Given no output schema, the description still tells the agent what to expect (job id) and how to proceed. It also covers the essential safety and validation constraints, making the tool usable without further lookups.

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

Parameters4/5

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

Schema description coverage is only 33%, but the description adds meaning for sha256 (must exactly match what open77_workshop_plan returned) and consent (human's explicit yes). planId is not elaborated, but its role as the identifier is reasonably inferable from the schema and name.

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 clearly states the action ('Installs a plan'), identifies the resource, and sets the precondition that the human has read and accepted it. It also names the related plan and job tools, which differentiates it from the sibling install/plan/release flow.

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

Usage Guidelines5/5

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

Explicitly states when it is safe to call ('Never call this without the human's explicit yes'), what inputs are required (consent=true and exact sha256), and what to do next ('follow it with open77_workshop_job'). This is strong practical guidance for an agent.

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