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Glama

proofite

by com.proofite

Ask why a story was missing

report_missing_story

The reader expected a story and the briefing did not have it. Describe it in their words; the editor investigates their own sources of the last days, today's briefing, their preferences and a web search, and answers with a verdict: it was in the briefing, none of their sources carried it (and proposes the missing source), it was dropped because of a preference (and corrects it), it was seen but undervalued, or it could not be found. Topics get followed so similar stories do not slip again; a deep-dive may be queued for the next briefing. Five per day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesWhat story they expected, in their own words
briefing_idNoWhich briefing it was missing from. Omit for the latest.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

The description goes well beyond the annotations by disclosing concrete side effects: the editor investigates sources and preferences, may follow topics, and may queue a deep-dive for the next briefing. It also mentions the five-per-day limit. These details meaningfully inform an agent about the tool's non-readonly behavior, complementing the readOnlyHint=false annotation.

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 dense but not bloated; every clause contributes useful information about what happens when the tool is invoked. The verdict categories and side effects are front-loaded enough, though the long middle sentence could be split for easier scanning.

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?

For a tool with only two parameters and no output schema, the description covers the trigger, the input semantics, the possible verdicts, the side effects, and the rate limit. An agent has enough context to invoke it appropriately and to interpret the likely result.

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%, so the schema already documents both text and briefing_id. The description adds little beyond reinforcing that the story should be described 'in their words'. This meets the baseline but does not exceed it.

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 tool's purpose: a reader reports a story they expected, and the editor investigates and returns a verdict about why it was missing. It enumerates the possible verdicts and side effects, which distinguishes it from sibling tools like request_deep_dive or correct_briefing.

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?

The opening sentence gives the exact trigger condition: the reader expected a story and the briefing did not have it. This tells the agent when to use the tool, though it does not explicitly contrast it with alternatives such as correct_briefing or request_deep_dive. Still, the context is clear enough to avoid major misuse.

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

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TDQS

A4.2/5.0
Disambiguation4/5

Most tools target distinct operations (e.g., add_feed vs. remove_feed, get_source vs. list_sources). However, there is some ambiguity between correct_briefing and tune_topic (both adjust content based on user feedback) and between request_deep_dive and correct_briefing (both can trigger deeper investigation). The descriptions help, but an agent could misselect.

Naming Consistency5/5

Tool names follow a very consistent verb_noun pattern (e.g., add_feed, create_source, generate_briefing, list_sources). All use snake_case with clear, descriptive verbs and nouns. No mixing of conventions.

Tool Count4/5

With 27 tools, the server covers a rich domain of news feed management, briefing generation, and user preferences. This is slightly above the typical sweet spot but still reasonable given the complexity. Each tool serves a distinct purpose; the count is justified.

Completeness5/5

The tool set provides full lifecycle coverage: sources can be created, read, updated, and deleted; feeds and searches can be added and removed; briefings can be generated, listed, read, rated, and corrected; deep dives and read-later items are supported. There are no obvious gaps—the domain is thoroughly covered.

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