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Clinicaltables

by io.github.pipeworx-io

Icd10cm

icd10cm
Read-onlyIdempotent

"What's the ICD-10 code for [diagnosis]" / "diagnosis code lookup" / "billing code for [condition]" / "EHR code for [X]" — search ICD-10-CM diagnostic codes (US clinical modification, ~96k codes). Returns code + full description. Use for medical billing, EHR diagnosis coding, claim coding. Example: terms="diab" → E11.9 Type 2 diabetes mellitus without complications.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dfNoComma-separated display fields to use in the `displays` array. Default varies per table; usually the canonical name.
efNoComma-separated extra fields to include per match. Field names vary per table; check NLM docs at clinicaltables.nlm.nih.gov.
countNoMaximum matches to return. Default 7, max 500. Use 1–3 for typeahead UX, 20–50 for browsing.
termsYesSearch query — prefix/contains match against canonical names. Whitespace-split into AND tokens. Example: "type 2 diabetes".

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds search behavior (prefix/contains match, AND tokens), return format (code + full description), and example output, exceeding annotation coverage.

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?

Description is compact, front-loaded with example queries, and every sentence adds value. 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?

For a simple lookup tool, all aspects are covered: purpose, parameters, behavior, output format, use cases. Schema annotations cover safety. No output schema needed as return value is described.

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 3. Description reinforces 'terms' parameter but adds little beyond schema. No additional semantics for df, ef, or count beyond what schema provides.

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?

Description explicitly states 'search ICD-10-CM diagnostic codes' with verb and resource, and provides example queries and use cases (medical billing, EHR coding). It distinguishes from siblings via name (ICD-10 vs ICD-9) and context.

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?

Clear use cases provided (medical billing, EHR diagnosis coding, claim coding). Lacks explicit when-not or alternatives like icd9cm, but the context is sufficient for an agent to decide.

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

A3.9/5.0
Disambiguation3/5

Several tool groups (ask_pipeworx/ask_pipeworx_grounded/deep_research, conditions/disease_names, polymarket_* family) have overlapping purposes, requiring careful reading of descriptions to differentiate. While many tools are conceptually distinct, the similarity within domains could lead to agent misselection.

Naming Consistency3/5

Naming is mostly snake_case but patterns vary: verb_noun (ask_pipeworx), noun_noun (entity_profile), single verb (forget, recall), and some adjectives (recent_changes). No consistent structure across the set, though individual names are descriptive.

Tool Count2/5

With 40 tools, the server is overly large for typical coherence. The tool count exceeds the 15–25 range deemed borderline, making it hard for agents to navigate and select efficiently.

Completeness4/5

The surface covers medical coding (ICD, LOINC, UCUM, drugs, procedures), financial data, prediction markets, memory, subscriptions, and meta-tools. Missing but minor elements (e.g., CPT codes) do not significantly hinder common workflows.

Resources