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Data Cambridge

by io.github.pipeworx-io

Cambridge Query

cambridge_query
Read-onlyIdempotent

Run a raw SoQL query against any Cambridge open-data resource (data.cambridgema.gov) by its Socrata id (8-char like "2z9k-mv9g"). Full SoQL: where/select/group/order/limit/offset. Use cambridge_datasets to find a resource id, or cambridge_recent for the common ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNoSoQL $group (e.g. "incident_category").
limitNoMax rows (default 100, max 5000).
orderNoSoQL $order (e.g. "incident_datetime DESC").
whereNoSoQL $where filter (e.g. "incident_year=2025").
offsetNoRow offset for paging.
selectNoSoQL $select (e.g. "incident_category, count(*)").
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.
resource_idYesSocrata resource id, e.g. "2z9k-mv9g" (police incidents).

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds transparency by explaining the optional _apiKey parameter and mentioning the keyless endpoint, which is behavioral context beyond the annotations. No contradiction.

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 three sentences with no wasted words. The first sentence front-loads the core action and resource. The second sentence succinctly lists the SoQL clauses. The third sentence directs to sibling tools. Every sentence earns its place.

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?

Given 8 parameters with full schema coverage and no output schema, the description provides enough context for an agent to use the tool. It explains the query capability, the resource identifier method, and how to obtain parameters. While it lacks an explicit mention of the output format (which is standard Socrata JSON), it is still reasonably complete for the complexity.

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 description coverage is 100%, so the baseline is 3. The description does not add significant new meaning per parameter; it merely enumerates the SoQL clauses. However, the overall context of 'Full SoQL' helps the agent understand the parameters collectively. This meets the minimum but does not exceed it.

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 ('Run a raw SoQL query'), the specific resource ('any Cambridge open-data resource'), and the identifier method ('Socrata id'). It also distinguishes itself from sibling tools 'cambridge_datasets' (for finding resource ids) and 'cambridge_recent' (for common ones).

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?

Explicitly tells when to use this tool (when you have a Socrata id and want to run a raw query) and when to use alternatives ('Use cambridge_datasets to find a resource id, or cambridge_recent for the common ones'). It also lists the SoQL clauses available, guiding the agent on how to structure queries.

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

A3.9/5.0
Disambiguation3/5

Most clusters have clear roles, and the detailed routing guidance separates ask_pipeworx from deep_research and grounded mode. However, three ask_pipeworx variants (one currently identical to stable), plus overlapping opportunity-discovery tools (polymarket_edges vs bet_research) and discovery/onboarding tools (discover_tools vs suggest_questions), leave several boundary cases where an agent could select the wrong tool.

Naming Consistency3/5

Many tools group under readable prefixes (ask_pipeworx, cambridge_, polymarket_, pipeworx_) and are mostly snake_case. But the set mixes bare verbs (remember, recall, forget), verb_noun actions (resolve_entity, validate_claim), and noun-phrase names (entity_profile, recent_changes, polymarket_fill_risk), so no single convention predicts the full API.

Tool Count2/5

34 tools is well into the 'too many' band, and the count is inflated by a kitchen-sink mix of data querying, prediction-market analysis, memory, subscriptions, feedback, llms.txt generation, and npm scanning. The server name 'Data Cambridge' suggests a narrow local-data scope, which makes the sprawl look even less appropriate.

Completeness3/5

Individual verticals are fairly complete: query/grounded/beta router levels, entity resolution/profile/compare/change, prediction-market discovery through fill-risk, and full memory and subscription CRUD. The major gap is discover_tools, which returns tools promoted as ready to call directly but no generic invocation tool is exposed, so the agent must route back through ask_pipeworx.

Resources