Skip to main content
Glama

report_store

Submit a trust-and-safety violation report when a store shows deceptive pricing, phantom stock, or invalid coordinates, so agents can flag discrepancies for review.

Instructions

Submit an autonomous trust-and-safety violation report if a store exhibits deceptive pricing, phantom stock, or invalid coordinates.

Input Schema

NameRequiredDescriptionDefault
detailsYesDetailed explanation of the discrepancy observed by the agent or user
categoryYesViolation category
store_idYesUUID of the store being reported
agent_sourceNoIdentifier of the reporting AI agentmeta_muse

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It says the report is 'autonomous' but never states what happens after submission—whether it is filed immediately, whether duplicates are rejected, whether the agent needs confirmation, or what permissions are required for a write operation against a store.

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?

A single front-loaded sentence with the verb first and the qualifying conditions immediately after; no filler and nothing repeated from the schema.

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?

For a mutation tool with zero annotations and no output schema, the description covers selection adequately but leaves the consequence side thin—the agent cannot tell what a successful submission returns or whether the report can be amended. The rich 100%-covered schema offsets some of that gap, keeping it at minimum-viable-plus.

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 store_id, category, details, and agent_source are already documented in the schema. The description's examples hint at which categories apply but add no syntax, format, or guidance for the details field or the agent_source default beyond what the schema supplies, so the baseline 3 is correct.

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?

Names a specific verb ('Submit') and resource ('trust-and-safety violation report') and enumerates the triggering conditions (deceptive pricing, phantom stock, invalid coordinates), which map onto the enum categories. The action is unmistakably distinct from the transactional siblings search_catalog, create_order, and check_order_status.

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 conditional clause 'if a store exhibits...' gives an explicit trigger for when to invoke it, which is more than most descriptions offer. It stops short of stating when not to use it (e.g., prefer other categories, or avoid duplicate filings) or naming any alternative route, so it falls short of a 5.

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