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Glama

Nihr

by io.github.pipeworx-io

Nihr Awards By Programme

nihr_awards_by_programme
Read-onlyIdempotent

Break UK NIHR funding down by programme or funding stream: award counts, total value in GBP, mean award size and the date range of awards in each. Called with no arguments it lists every NIHR programme that actually exists with its totals, which is the way to discover valid programme names before filtering elsewhere. Answers "which NIHR programme spends the most", "how many awards has the Health Technology Assessment programme made", and "what NIHR fellowship schemes exist and how big are they".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax groups to return, 1-100 (default 30).
filterNoOnly include groups whose name contains this case-insensitive substring, e.g. "Fellowship", "Public Health", "Global".
sort_byNoOrdering of the groups (default total_desc, biggest spend first).
group_byNoField to aggregate on (default "programme"). "funding_stream" is the finer-grained scheme name; "programme_type" splits Research from Career Development.
start_fromNoOnly aggregate awards starting on or after this date, YYYY-MM-DD.
project_statusNoRestrict the aggregation to one status: Active, Complete, Contracted or Discontinued.

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: -[
-  {
-    "group_by": "programme",
-    "limit": 10,
-    "sort_by": "total_desc"
-  }
-]New value: +[
+  {
+    "group_by": "programme",
+    "limit": 10
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, etc. The description adds behavioral context by explaining the discovery pattern (no arguments lists all programmes) and that it aggregates data, which goes beyond the 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 a single coherent paragraph that front-loads the core function. It is concise and every sentence adds value, though it could be slightly more structured for readability.

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 optional parameters and no output schema, the description adequately explains the tool's purpose, usage pattern, and output fields (counts, total value, mean size, date range). It fully covers what an agent needs to know.

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?

All 6 parameters are fully described in the input schema (100% coverage). The description does not add additional meaning to individual parameters beyond what the schema already 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 clearly states it breaks down UK NIHR funding by programme or funding stream, providing award counts, total value, mean size, and date range. It gives concrete example questions and distinguishes from sibling tools like nihr_awards_by_organisation.

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 calling with no arguments lists every programme to discover valid names before filtering. It provides example questions but does not explicitly state when not to use or list alternatives, though the sibling context is available.

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

A3.7/5.0
Disambiguation2/5

The set contains several clusters of near-overlapping tools: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, ask_pipeworx/deep_research/validate_claim all handle natural-language queries, and bet_research/polymarket_edges/polymarket_arbitrage scan the same prediction-market space. The descriptions are detailed, but that does not remove the boundary confusion.

Naming Consistency4/5

Almost all tools use lowercase snake_case with recognizable patterns such as verb_noun or prefix_domain (nihr_, polymarket_, pipeworx_). There are minor deviations like ask_pipeworx_beta vs ask_pipeworx_grounded and mixed noun/verb phrasing, but the naming is predictable overall.

Tool Count2/5

36 tools is beyond the typical well-scoped server size, and the set reads as several products bundled together: NIHR grants, Pipeworx data research, prediction markets, memory, subscriptions, and standalone utilities like generate_llms_txt or scan_dependency. Even for a broad data platform this is too many to navigate coherently, and it is a severe mismatch for a server named 'Nihr'.

Completeness3/5

Within its subdomains the set covers core workflows: query (ask/deep_research/validate), entity resolution/profile/comparison, NIHR grant lookup by several dimensions, prediction-market analysis through fill-risk, and memory/subscription lifecycles. But it is a collection of partial products rather than one coherent domain, and some outputs such as pipeworx:// citations or detected arbitrage opportunities lack an obvious in-set tool to consume them further.

Resources