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Glama

Iso

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description adds value by describing return format ('top-N most relevant tools with names, descriptions, and full input schemas') and noting that results are 'ready to call directly'. No contradictions with annotations.

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 front-loaded with purpose and includes a list of domains and usage guidance. While somewhat long, every sentence is relevant and structured logically. Could be slightly more concise but no wasted words.

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?

Given the tool's role as a discovery tool, the description fully covers input (natural language query), output (top-N tools with schemas), and usage context (call first when unsure). No output schema exists, but the description compensates by explaining what is returned.

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 baseline is 3. The description mentions that query accepts natural language and lists aliases, but the schema already provides identical information. The description adds no meaning beyond the schema.

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 finds tools by describing data or task, listing many example domains. It distinguishes itself from siblings by being a meta-discovery tool, as seen in the explicit instruction 'Call this FIRST when you have many tools available'.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available and want to see the option set (not just one answer)'. This clearly differentiates when to use this tool versus directly using a specific tool.

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

All Iso toolsInspect
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TDQS

A3.6/5.0
Disambiguation3/5

Tools are mostly distinct but there is some overlap among lookup tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) and among Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage). Agents might occasionally struggle to choose the right one.

Naming Consistency2/5

Naming is inconsistent: some use verb_noun snake_case (ask_pipeworx, compare_entities), some are single words (forget, recall, remember), and others are noun-based (compliance_catalog, entity_profile). No consistent pattern.

Tool Count1/5

With 34 tools, the count is too high for a server named 'ISO Standards'. The majority of tools are unrelated to ISO standards (e.g., Polymarket, memory, web scraping), making the scope highly inappropriate.

Completeness1/5

As an ISO standards server, the tool set is severely incomplete. Only 4-5 tools (search_standards, get_standard, compliance_catalog, open_data_files) actually deal with ISO standards. Essential operations like comparing standards or browsing revisions are missing.

Resources