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Glama

flood

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.

Schema Changelog

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

  1. Changed5 schema fields changed
    • addedInput schema / properties / description
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
    • addedInput schema / properties / q
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
    • changedInput schema / properties / query / description
      Previous value: -"Natural language description of what you want to do (e.g., \"analyze housing market trends\", \"look up FDA drug approvals\", \"find trade data between countries\")"New value: +"Natural 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."
    • addedInput schema / properties / search
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
    • addedInput schema / properties / task
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "look up FDA drug approvals"
+  },
+  {
+    "query": "analyze housing market trends"
+  }
+]
  3. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: returns top-N results with full input schemas, ready to call directly, no second lookup needed. This tells the agent exactly what to expect in the response, which is not conveyed by the annotations alone.

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 moderately long but every sentence serves a purpose: purpose, usage context, return value detail, and a strong 'call this FIRST' directive. The domain list is somewhat extensive but directly helps the agent decide relevance. No fluff, but slightly over the minimal length, earning a 4 rather than 5.

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 there is no output schema, the description adequately explains the return value (top-N tools with names, descriptions, and full input schemas). It also covers when to use it, and the annotations cover safety. For a discovery tool, this is complete: purpose, usage, and expected output are all addressed, with no obvious gaps.

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 100%, so the schema fully documents the parameters. The description mentions 'top-N' and 'query' as natural language, but these are already present in the schema descriptions. The description does not add significant new meaning about parameter syntax, types, or aliases beyond what the schema provides, so baseline 3 is appropriate.

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 opens with a specific verb and resource: "Find tools by describing the data or task." It clearly distinguishes this as a meta-tool for browsing/discovering other tools, and enumerates many concrete domains (SEC filings, FDA drugs, FRED, etc.), making it unmistakable what this tool does and how it differs from sibling tools.

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 explicitly states when to use: "Use when you need to browse, search, look up, or discover what tools exist for..." and "Call this FIRST when you have many tools available and want to see the option set (not just one answer)." This provides clear context and implies a distinction from using a specific tool directly, though it doesn't list explicit exclusions.

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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TDQS

A3.6/5.0
Disambiguation2/5

Several tool clusters have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and polymarket_kalshi_spread all analyze prediction-market opportunities; discover_tools and suggest_questions both serve as meta-tool onboarding. An agent could easily pick the wrong variant.

Naming Consistency3/5

Most tools use snake_case, but naming patterns are mixed: some are verb_noun (get_flood_forecast, list_subscriptions), some are noun-centric (entity_profile, bet_research), some are bare verbs (remember, recall, forget), and some use long descriptive phrases (ask_pipeworx_grounded, polymarket_kalshi_spread). It is readable but lacks a single predictable convention.

Tool Count2/5

33 tools is heavy for a server whose apparent core is flood forecasting — only 2 of 33 tools (get_flood_forecast, get_river_discharge) relate to flooding. The bulk is a sprawling Pipeworx data-access, prediction-market, and memory layer, making the surface feel overstuffed and off-topic relative to the server name.

Completeness2/5

If the intended domain is flood data, the surface is severely incomplete: only forecast and discharge lookups exist, with no historical flood events, alert subscriptions, mapping, or severity-warning tools. If instead the domain is meant to be Pipeworx-style data research, the surface is broad but still has gaps (no direct SEC filing text retrieval, no clear update/delete lifecycle for many resources). Either way, the purpose is unclear and coverage is mismatched.

Resources