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Glama

feedback

FREE feedback: tell us what you needed but didn't get (missing endpoint, wrong output shape, price objection, bug). No payment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wantedYes
contactNo
contextNo
categoryNoother

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.5/5.0
Behavior2/5

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

With no annotations provided, the description fully bears the transparency burden. It reveals the tool is free and non-payment-related, but does not disclose whether feedback is anonymous, how it gets processed, whether multiple submissions are allowed, or any rate limits. The lack of behavioral context (e.g., 'This is a one-way communication; no guaranteed response') leaves the agent under-informed.

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 two sentences long with no filler. Front-loaded with the key action 'FREE feedback', followed by a concise list of examples. However, the phrase 'No payment' repeats the concept of 'FREE' and could be removed for even tighter structure.

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?

Given the tool's low complexity and presence of an output schema (which presumably handles return value documentation), the description covers the basic purpose and some affordances. However, the complete lack of parameter documentation and behavioral transparency makes it merely adequate, not complete.

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

Parameters2/5

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

Schema description coverage is 0%, meaning the description must compensate for all four parameters. It only mentions 'wanted' implicitly via the feedback request and fully ignores 'contact', 'context', and 'category'. The agent has no guidance on format, constraints, or how to fill these fields beyond the schema's basic names.

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: collecting user feedback about missing endpoints, wrong output shapes, price objections, or bugs. The verb 'tell us what you needed but didn't get' is specific, and the examples disambiguate from the 16 sibling tools, none of which suggest feedback collection.

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 description explicitly says 'FREE feedback' and 'No payment', which guides usage when to use it (free-form feedback) and hints at when not to (not for paid requests). However, it does not explicitly contrast with siblings or state exclusions like 'do not use for general support questions'.

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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Add one secure layer between your agents and this server.

TDQS

C2.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: financial data tools (calendar, candles, earnings, etc.) are separate from web scraping tools (read, screenshot, unlock, etc.). However, there is some overlap between 'history' (daily closes + range change) and 'candles' (OHLCV), which could cause minor confusion.

Naming Consistency2/5

Tool names are inconsistent: most are single-word nouns (e.g., 'calendar', 'candles') but some are verbs ('read', 'search', 'unlock') and one uses an underscore ('url_safety'). There is no uniform verb_noun or noun pattern, making it harder for an agent to predict tool names.

Tool Count4/5

With 16 tools, the server is slightly above the ideal range of 3-15, but each tool appears to serve a distinct purpose. The count is manageable given the two domains (financial data and web scraping).

Completeness3/5

The financial data tools cover many common data points (economic releases, price history, filings, earnings) but miss order books, real-time trades, or news. The web scraping tools are comprehensive for fetching content but lack structured data extraction. The feedback tool suggests the server is still evolving, indicating notable gaps.

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