foundation-discovery

Find Funders for Peer Orgs

find_funders_for_peers

Read-only

Find grantmakers that have ACTUALLY funded organizations LIKE the caller's, using the real 7.5M-edge who-funds-whom grant graph (IRS 990-PF, 2022-2026). This is the strongest free-tier prospecting move: collaborative-filtering peer prospecting, distinct from search_funders (name/topic lookup) and search_open_grants (active RFPs).

HOW IT WORKS: for each peer organization, it looks up every foundation that granted to that peer, then merges funders across peers. A funder that gave to several of your peers ranks highest. Every result carries real grant evidence — which peers the funder funded and for how much.

INPUTS (provide one):

peer_orgs (PREFERRED): names or 9-digit EINs of organizations LIKE the one you're raising for — peers, aspirational orgs, or orgs with a similar mission. The graph is keyed by recipient EIN, so naming real peers yields the sharpest evidence. Up to 12 are used.
org_description: a SHORT CAUSE PHRASE, not a paragraph — "food bank", "mental health", "affordable housing". Fallback for when you cannot name peers: it matches the phrase against IRS BMF organization NAMES and, if that finds nothing, against the NTEE cause taxonomy, then uses the best-funded organizations in that cause (biased to location). It does NOT search mission text, so a LONGER description matches FEWER orgs, not more — keep it to the cause, and prefer peer_orgs. The response reports which pass produced the peers in peer_discovery.

RECOMMENDED WORKFLOW: establish the org's mission/cause, then name 2-5 peer organizations and call this tool. Deepen any candidate with get_funder_profile / get_foundation_grants (pass the returned ein).

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of funders to return (1-50)
`location`	No	Optional 2-letter state or "City, ST". Only biases peer discovery under org_description; never filters funders.
`peer_orgs`	No	Names or EINs of peer / aspirational organizations. Example: ["Greater Chicago Food Depository", "Feeding America"].
`min_amount`	No	Minimum single-grant size in USD (default 5000)
`org_description`	No	Short cause phrase for the nonprofit (fallback). Example: "youth mental health". Adding words narrows the match.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already mark this as read-only and non-destructive, and the description adds substantial behavioral context beyond that: the 7.5M-edge graph, 2022-2026 IRS data, how funders are merged across peers, that results carry grant evidence, that location only biases peer discovery and never filters funders, and that longer org descriptions match fewer orgs. This is unusually transparent.

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 longer than average but earnestly structured with bold section labels and front-loaded purpose. Each section adds operational value; only minor marketing-style phrasing like 'strongest free-tier prospecting move' is non-essential. Overall it is dense but well-organized.

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 tool with 5 optional parameters, a fallback matching algorithm, and sibling alternatives, the description is complete: it covers inputs, behavior, edge cases, recommended workflow, and downstream follow-up tools. Since an output schema exists, not spelling out return fields is acceptable, and the description even names a returned field (peer_discovery).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is already 100%, and the description still adds meaningful guidance: peer_orgs is preferred, up to 12 are used, org_description should be a short cause phrase rather than a paragraph, and the matching fallback path is explained. This goes well beyond the schema's field descriptions, especially for the two mutually-conditioned input modes.

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?

States a specific verb and resource: 'Find grantmakers that have ACTUALLY funded organizations LIKE the caller's' using a named grant graph. It also explicitly distinguishes this tool from search_funders and search_open_grants, so an agent can immediately tell it apart from siblings.

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?

Gives explicit when-to-use guidance: name 2-5 peers for sharpest results, use org_description only as a fallback, and pair with get_funder_profile/get_foundation_grants for deeper research. It also names the alternatives it is not (search_funders, search_open_grants), making selection unambiguous.

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

A4.4/5.0

Disambiguation5/5

Each tool serves a distinct purpose: find_funders_for_peers uses peer-based collaborative filtering, search_funders does name/topic lookup, search_open_grants finds active RFPs, search_nonprofits searches recipients, get_funder_* tools provide different aspects of funder data, and utilities like health_check and list_tools are separate. No overlap.

Naming Consistency3/5

Naming conventions are mixed: 'find_', 'get_', 'search_', 'health_check', 'list_tools', 'get_ntee_codes'. While verbs are descriptive, there is no single consistent pattern (e.g., all search_ or all get_). This could cause slight confusion.

Tool Count5/5

12 tools is well-scoped for a foundation discovery server. Each tool addresses a clear need (prospecting, detail, financials, jobs, utilities) without being excessive or insufficient.

Completeness5/5

The tool set covers the full lifecycle of foundation research: finding funders (by peers, name, open grants), getting detailed profiles, grants, stats, financials, NTEE codes, and even funder jobs. The inclusion of recipient-side search (search_nonprofits) complements the funder side, leaving no obvious gaps.

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