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GrantConnect (Australia)

Au Grants Top Recipients

au_grants_top_recipients
Read-onlyIdempotent

Rank the organisations that received the most Australian Commonwealth grant money, by total AUD awarded, with award counts and the agencies that funded them. Filter by agency, category, recipient_state, and an awarded_from/awarded_to date range. The response states how many award rows were scanned and whether that covered every matching row, so a ranking drawn from the largest awards can be told apart from a ranking over the complete set. Answers "who are the biggest recipients of federal grant funding in this portfolio, state or year".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many recipients to rank (1-100, default 20).
agencyNoFunding agency, substring match, e.g. "Department of Social Services".
categoryNoGrant category, substring match, e.g. "Social Inclusion".
awarded_toNoLatest publish date, ISO YYYY-MM-DD.
scan_limitNoHow many award rows to read before ranking, largest-value first (1000-20000, default 5000). Raise it for a ranking that covers more of the matching set.
awarded_fromNoEarliest publish date, ISO YYYY-MM-DD.
recipient_stateNoRecipient state/territory: ACT, NSW, VIC, QLD, SA, WA, TAS, NT.
include_aggregateNoDefault false. GrantConnect files bundled disclosures under the literal recipient name "Aggregate" when the individual recipients are withheld; those rows are excluded from the ranking because they are a reporting artefact rather than an organisation. Set true to count them as one pseudo-recipient.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses that the response includes the number of award rows scanned and whether all matching rows were covered, providing transparency about partial results. This complements the readOnlyHint and idempotentHint annotations without contradicting them.

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?

Three sentences, front-loaded with the main action, and every sentence adds value: the ranking purpose, filtering and scan behavior, and the answering of a common question. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core purpose, filters, output characteristics (award counts, agencies, coverage indicator), and an example question it answers. It lacks explicit return format details, but the absence of an output schema is partially mitigated by the description's mention of scanned rows and counts.

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%, and each parameter has a description. The tool description reinforces the date-range and scan_limit concepts but does not add significant extra meaning beyond the schema, justifying the baseline score.

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 ranks organisations by total Australian Commonwealth grant money received, with award counts and funding agencies. This specific verb+resource+scope distinguishes it from siblings like au_grants_by_recipient, which focuses on per-recipient grants rather than top recipients.

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 specifies filtering by agency, category, state, and date range, and explains the scan_limit nuance that helps users understand when a ranking is partial. It does not explicitly compare against alternatives, but the context is clear enough for selection.

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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