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Glama

Nihr

by io.github.pipeworx-io
OverviewAdmin

Nihr Award Holders

nihr_award_holders
Read-onlyIdempotent

Find the researchers named on UK NIHR awards by personal name or ORCID identifier. Returns each matching award holder with their ORCID, their role on the award (Chief Investigator, Joint Lead Applicant or Award Holder) and the NIHR project ids they hold, so an agent can pivot straight into nihr_get_award for the grant detail. Answers "which NIHR grants does Professor X hold", "who is the chief investigator on this NIHR award", and ORCID-to-grant lookups across 12,644 award-holder records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoResearcher name or any part of it, e.g. "Hajat", "Emma Bland". Titles such as Professor and Dr are part of the stored name and may be included or omitted.
limitNoMax award holders to return, 1-100 (default 20).
orcidNoORCID identifier in full, e.g. "0000-0002-3086-362X".
offsetNoPagination offset (default 0).
project_idNoNIHR project id, e.g. "NIHR208893" or "002/0028", to list everyone named on that one award.
involvement_typeNoRestrict to one role: "Chief Investigator", "Joint Lead Applicant" or "Award Holder".

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "name": "Hajat"
-  }
-]New value: +[
+  {
+    "limit": 10,
+    "name": "Steptoe"
+  },
+  {
+    "project_id": "NIHR205461"
+  }
+]
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The description aligns with all annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint false) and adds behavioral context: it returns matching award holders with their ORCID, role, and project IDs, and mentions the data size (12,644 records). No contradictions.

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?

The description is two sentences, front-loaded with purpose and method, then details returns and examples. Every sentence adds value with no fluff.

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 6 parameters (none required), no output schema, and simple query functionality, the description is complete. It explains input methods, return fields, and example queries, enabling the agent to understand how to invoke the tool and interpret results.

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 already documents all 6 parameters. The description adds minor nuance for the 'name' parameter (titles may be included or omitted) and provides examples, but overall adds limited value beyond the schema. 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 clearly states the verb 'find', the resource 'researchers named on UK NIHR awards', and the methods 'by personal name or ORCID identifier'. It specifies what is returned (ORCID, role, project IDs) and gives concrete query examples, distinguishing it from siblings like 'nihr_get_award' and 'nihr_search_awards'.

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 includes explicit use cases: 'which NIHR grants does Professor X hold', 'who is the chief investigator', and ORCID-to-grant lookups. It also mentions pivoting to 'nihr_get_award' for grant detail. However, it does not explicitly state when NOT to use this tool or what alternatives exist among siblings, so slightly lower.

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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