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company_listings

Inspect or advance company listings through their scoped lifecycle with verified receipts. Manage operations to list, update, or advance status.

Instructions

Inspect or advance listings through its scoped lifecycle and verified receipts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nowNo
engineNo
operationNolist
entity_refNo
project_idYes
bundle_jsonYes
payload_jsonNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Addedv0.1.1

TDQS

D1.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the burden of disclosing effects. 'Advance listings' does imply state-changing behavior, but there is no mention of prerequisites, side effects, idempotency, irreversibility, permissions, or what 'verified receipts' actually entails. The implication of lifecycle mutation is present but insufficiently detailed.

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

Conciseness2/5

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

The description is short, but brevity comes at the cost of utility; the sentence is under-specified and does not earn its place because it replaces clarity with domain jargon. This is under-specification rather than effective conciseness.

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

Completeness1/5

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

For a 7-parameter stateful tool with no annotations and 0% schema coverage, the description should compensate substantially. It does not mention lifecycle stages, allowed operations, receipt semantics, or required bundle fields, so an AI agent lacks enough context to call the tool correctly despite the output schema.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain any of the 7 parameters. There is no guidance on operation values, bundle_json structure, payload_json, entity_ref, engine, now, or project_id, so an agent cannot construct a valid invocation correctly.

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

Purpose2/5

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

The description names a verb and resource ('inspect or advance listings') but buries it in opaque phrasing ('scoped lifecycle and verified receipts') that does not clarify what a listing is or what advancing one means. It also fails to distinguish this tool from the many sibling listing/company tools, so an agent cannot confidently identify its purpose.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool, when not to use it, or which sibling is the alternative. With dozens of similar company_* and listing-related tools, the agent is left to guess based on name alone.

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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