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Glama
ppt-generator
by haandol

prepare_deck_review

Prepares a read-only grounding and narrative review for an entire deck, checking evidence, assumptions, duplicate content, terminology, agenda/body/closing alignment, and time density.

Instructions

Prepares one read-only grounding and narrative review for the whole deck.

Generate JSON matching the returned response_schema, then call ingest_deck_review. This checks evidence, assumptions, duplicate content, terminology, mandatory agenda/body/closing alignment, and time density.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>"
    },
    "name": "prepare_deck_review"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.2

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral load; it does disclose 'read-only' and that it emits a schema-conformant payload rather than mutating the project, which is genuinely useful. It does not say whether the call is idempotent, whether it consumes LLM budget, or what preconditions on project state apply.

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?

Purpose is front-loaded in one sentence, followed by the required follow-up call and the checklist of what is validated. No padding, though 'grounding' and 'narrative review' are somewhat jargon-laden terms that are not defined.

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

Completeness3/5

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

An output schema exists, so return values needn't be explained, and the two-step prepare→ingest protocol is spelled out. Missing pieces are the preconditions for calling it and any disambiguation from the sibling `prepare_review`, which matter given the dense family of prepare_/ingest_ pairs.

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

Parameters2/5

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

Schema description coverage is 0%, so the schema carries no documentation for `project_id`, and the description never mentions the parameter or its role. The tool is simple enough (single required string) that an agent can infer it, but the description does nothing to compensate for the coverage gap as required for low-coverage schemas.

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

Purpose4/5

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

States a specific verb (prepares), resource (deck review) and scope (whole deck), then enumerates the dimensions checked: evidence, assumptions, duplicates, terminology, agenda/body/closing alignment, time density. It clearly separates itself from `ingest_deck_review` via the prepare→ingest handoff, but does not distinguish itself from the sibling `prepare_review`, leaving ambiguity between deck-level and possibly narrower reviews.

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?

Gives an explicit workflow: generate JSON matching response_schema, then call `ingest_deck_review`. That is clear context for when and how to use it. It stops short of stating exclusions or prerequisites (e.g. whether a deck must already exist, or when to choose `prepare_review` instead).

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