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Glama

reader_ops

Check your daily reading inbox, starred items, stats, and search RSS articles by text or meaning from one endpoint. Start background RAG index sweeps and monitor job status.

Instructions

reader_ops - Daily reading surface: inbox, stars, search, stats, RAG sweeps.

RATIONALE: single entry point for what a human checks every morning.

Return Format

{success, message, items/stats/job/job_id/status/chunks}

Examples

  • {"operation": "inbox"} unread items

  • {"operation": "search_text", "query": "vienna"} FTS search

  • {"operation": "search_semantic", "query": "rocket engine"} vector search

  • {"operation": "trigger_sweep", "mode": "incremental", "hours": 4} background index job

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ctxNo
modeNoSweep mode: incremental or full. Used by: trigger_sweepincremental
hoursNoLookback hours for incremental sweep. Used by: trigger_sweep
limitNo
queryNo
job_idNo
feed_idNoScope sweep to one feed id, 0 means all. Used by: trigger_sweep
operationYesReader operation to run

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations at all, the description carries the full behavioral burden. It does disclose something valuable: trigger_sweep creates a background job (job/job_id/status in the return shape), implying async behavior the caller must poll. It says nothing about permissions, cost, or what a sweep mutates.

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?

Front-loads the purpose, then return format, then concrete request examples — a sensible structure for a dispatch tool. The RATIONALE line and the return-format block are somewhat redundant given an output schema exists, but nothing is badly bloated.

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 multiplexed tool the key requirement is mapping operations to payloads, and it gives that. The returns are covered by an output schema...

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 coverage is 50%, and the schema itself already tags mode/hours/feed_id with "Used by: trigger_sweep." The examples add a useful param-to-operation mapping (query paired with search_text/search_semantic, mode/hours with trigger_sweep), but limit, job_id, and ctx remain undocumented anywhere. Marginal value over the schema.

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?

The description names the resource (reading surface) and enumerates the concrete operations it multiplexes: inbox, stars, search, stats, RAG sweeps. It is clearly a single dispatch entry point rather than a tautology. It stops short of distinguishing itself from siblings like feeds_ops or readability_ops, so an agent must infer the boundary.

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

Usage Guidelines3/5

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

"Single entry point for what a human checks every morning" implies a daily-triage usage context, which is genuine guidance. However, it never states when to prefer feeds_ops/readability_ops, nor any exclusions or prerequisites (e.g., when a sweep is appropriate vs. an index query). Usage is implied, not prescribed.

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