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Glama

list_rfis

Read the RFI register before raising a question: retrieve each RFI's status, sheet, raiser, pending agent acceptance, linked markup IDs, finish tags, and withdrawn numbers.

Instructions

Every RFI in the register with its status, sheet, who raised it (actor) and whether an agent-raised one is still pending the estimator's acceptance, its linked markup ids, and the finish tags those markups are attached to — the scopes the question touches. withdrawn[] lists the numbers delete_rfi tombstoned, so a gap in the sequence is explained rather than silent. Read this before raising a question the register already holds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
openYesStill awaiting an answer
rfisYesEvery live RFI, register order
countYes
pendingYesAgent-raised and not yet accepted by an estimator
withdrawnYesNumbers of withdrawn RFIs (delete_rfi tombstones) — the gaps in the sequence, explained

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.21

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses the returned fields, the meaning of withdrawn[] (tombstoned by delete_rfi), and the pending-acceptance state of agent-raised RFIs. It does not state read-only/authorization behavior explicitly, but the rich semantic disclosure is strong.

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

Conciseness3/5

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

It is front-loaded and every clause carries information, but it is a single dense sentence with multiple em dashes and parenthetical asides. The lack of sentence breaks makes it harder to parse than necessary, and some return-field detail is redundant with the output schema.

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 a zero-parameter tool with an output schema and no annotations, the description supplies the semantic context an agent needs: what an RFI listing contains, what the withdrawn[] gap means, and when to consult it before creating a new RFI. Nothing essential is missing.

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?

The tool has zero input parameters, so there is no parameter semantics to explain; the empty schema's 100% coverage makes the baseline 4. The description appropriately does not invent parameter guidance.

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 states a specific verb-and-resource pairing: listing every RFI in the register with explicitly enumerated attributes. It distinguishes the tool from siblings like create_rfi and delete_rfi by scoping it as the read-before-you-raise view and by explaining that delete_rfi tombstones entries.

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 gives a clear trigger — 'Read this before raising a question the register already holds' — which routes the agent away from create_rfi when the register may already contain the answer. It does not name any explicit exclusion or alternative beyond that implication, so it falls short of full when/when-not guidance.

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