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DC Member API

by io.github.dynamitecircle

profile_match_create

POST /profile-match — Match DCers from a description (or recommend if omitted)

AI-powered profile matchmaker. Match DCers against a natural-language description, or — when query is omitted — recommend DCers based on your own profile (chapter, industry, expertise, goals).

Returns ranked results from a profile-vector search (Gemini embeddings + reranking under the hood). The caller's LLM synthesizes any narrative on top. Stricter rate limits than the standard CRUD endpoints because of the embedding/rerank cost.

Two modes:

  • With query: free-form description ("DCers in Lisbon who run SaaS").

  • Without query: AI builds an implicit query from your profile and returns "DCers you should meet". Useful for cold-start "who should I message this week?" prompts.

Optional structured filters (combine with either mode, all AND-ed):

  • locationChapterPlaceID — narrow to DCers whose home / base location matches this Google Place ID. Use for "based in X" queries. Resolve via GET /places/search.

  • locationCurrentPlaceID — narrow to DCers currently in this place (auto-derived from their last GPS / active trip). Use for "currently in X" / "visiting X" queries.

  • eventID — narrow to DCers holding a valid ticket to this event ("DCers attending DCMEX who run logistics"). Refunded / canceled tickets are excluded.

  • isDCB — when true, narrow to DC BLACK members only.

  • businessIndustry — exact match on the DCer's primary business industry.

  • minTeamSize — "at least this size" filter on team headcount (only matches DCers whose team-size visibility is shared with all DCers).

  • minAnnualRevenue — "at least this revenue" filter on annual revenue (only matches DCers whose revenue visibility is shared with all DCers).

  • gender — exact match on the DCer's self-reported gender. Note: Gender is sparsely populated — most DCers leave it blank. Use this as a "narrow if set" hint rather than a hard requirement; combine with query for best results.

⚠️ WRITE operation: this mutates your DC account data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
isDCBNoOptional. When `true`, narrows results to DC BLACK members only.
limitNoMax results (1-50, default 50). Hard cap at 50 — match is expensive; narrow with filters instead of paginating.
queryNoFree-form description of the DCers you want to find. Omit to get recommendations based on your own profile.
genderNoOptional. Exact-match filter on the DCer's self-reported gender. Allowed values: `Man`, `Woman`, `Non-binary`, `Prefer not to say`. **Note: Gender is sparsely populated — most DCers leave it blank** — combine with `query` rather than relying on this alone.
eventIDNoOptional. DC event ID — narrows results to DCers with a valid ticket (RSVP yes/maybe or paid). Pair with `query` for "DCers attending X who do Y".
minTeamSizeNoOptional. "At least this team size" filter — matches DCers whose team-size bucket is >= this value, ordered as `None < 1-2 < 3-5 < 6-9 < 10-14 < 15-19 < 20-34 < 35-49 < 50-74 < 75-99 < 100+`. `Prefer not to say` also exists in the bucket vocabulary but is treated as "unknown" and always filtered out. Only DCers who set their team-size visibility to "all DCers" are matched; the rest are excluded silently.
skipRerankingNoOptional. When `true`, skip the keyword reranker and return results in raw vector-similarity order. Useful when the query is fuzzy/semantic (where exact keyword overlap would add noise) or when comparing reranked vs raw ordering.
businessIndustryNoOptional. Exact-match filter on the DCer's primary business industry. Allowed values: `SaaS & Tech`, `Marketing Agency`, `Productized Services`, `Ecommerce & Amazon`, `Courses and Info Products`, `Affiliate, Content Creation, or Ad Revenue`, `Professional Services & Industry Specific Consulting`, `Real Estate and Investing`, `Coaching`, `Other`.
minAnnualRevenueNoOptional. "At least this revenue" filter on annual revenue. Pass any revenue label (e.g. `$1M+`, `$250K+`, `$100K+`); the filter parses to a number and matches DCers at-or-above. Only DCers who set their revenue visibility to "all DCers" are matched; the rest are excluded silently.
locationChapterPlaceIDNoOptional. Google Place ID — narrows results to DCers based here ("based in X"). Resolve via `GET /places/search`.
locationCurrentPlaceIDNoOptional. Google Place ID — narrows results to DCers currently here, whether they live there or are visiting. **Sparsely populated** — `currentLocation` is self-reported and most DCers leave it null, so this filter under-recalls. For "who is in <city> right now?" prefer creating a trip via `POST /trips` and reading `GET /trips/:tripID` — the `discovery.fullPool` block lists locals AND visitors during the trip window. Resolve placeIDs via `GET /places/search`.

TDQS

A4.8/5.0
Behavior5/5

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

Discloses AI-powered nature, write operation, mutation of account data, rate limits, and limitations of filters like gender and location. No annotations exist to contradict.

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?

Well-structured with sections and bullet points, but somewhat lengthy. Front-loaded with key info; each sentence adds value.

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?

Covers both modes, filter behaviors, rate limits, and limitations. Lacks output schema but describes return type ('ranked results'). Sufficient for the tool's complexity.

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?

Adds significant context beyond the schema: explains modes, how filters interact, when they under-recall, and how to combine them. Schema coverage is 100% but description enriches every parameter.

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's purpose: matching DCers based on a natural-language description or recommending based on the user's profile. It distinguishes two modes and contrasts with sibling tools like search_profiles.

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?

Provides explicit guidance on when to use each mode, warns about rate limits and sparsely populated filters, and suggests alternative tools (e.g., trips for current location).

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
Disambiguation4/5

Despite the large number of tools, each has a detailed description that clearly distinguishes its purpose. Minor potential overlaps (e.g., search vs. resource-specific search, own vs. other's agenda) are well documented, so an agent can differentiate them.

Naming Consistency4/5

Tool names follow a consistent verb_noun or resource_subresource_action pattern in snake_case. A few tools are just nouns (e.g., 'alerts', 'announcements'), but these are top-level listing endpoints; overall the naming is predictable.

Tool Count2/5

85 tools is very high for a single server, making it difficult for an agent to efficiently explore and select the right tool. While each tool seems justified for the broad domain, the count feels overwhelming and could be streamlined.

Completeness3/5

The tool surface covers most major areas (events, trips, chapters, rooms, search, profile, etc.) with CRUD or lifecycle operations. However, the lack of a 'send message' tool for rooms is a notable gap, and some resources (e.g., events) are read-only on creation/update, limiting agent workflows.

Resources