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Fmp

by io.github.pipeworx-io

Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

TDQS

A3.9/5.0
Behavior1/5

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

The description contradicts the annotation `readOnlyHint: true`. The description states that setting `mark_read:true` will flag events as read, causing the next call to show only newer events — a state-changing side effect. This directly contradicts the read-only hint, constituting an annotation 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 well-structured, starting with the core action in the first sentence, then providing return details, filtering options, a side-effect note, and an alternative access method. Every sentence adds useful information without redundancy, and it is appropriately sized.

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 the tool's complexity (5 optional parameters, no output schema), the description covers purpose, return payload composition, filtering, side effects of mark_read, and an alternative endpoint. It also mentions polling suitability, making it sufficiently complete for an agent to select and invoke the tool correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds value by giving a concrete example for `type` ('sec_8k'), confirming `since` expects an ISO timestamp, and explaining the side effect of `mark_read` in plain language, which is helpful beyond the schema descriptions.

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 with a specific verb ('Pull fired events from your subscription feed') and resource ('subscription feed'). It distinguishes itself from siblings like list_subscriptions and recent_changes by focusing on fired alerts with filtering options.

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 provides clear context for when to use the tool, mentioning polling suitability and an alternative HTTP endpoint for scripts/dashboards. However, it does not explicitly name excluded use cases or directly contrast with sibling tools, so it stops short of a perfect score.

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

C2.5/5.0
Disambiguation2/5

Multiple tools overlap in purpose: quote/quote_short/historical_price/intraday for price data; balance_sheet/income_statement/cash_flow for financials; search_symbol/search_name/discover_tools for lookup; and a cluster of Pipeworx routers (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim) with unclear boundaries. Agents will frequently select the wrong tool.

Naming Consistency3/5

All tool names use consistent snake_case, but naming conventions vary widely: noun phrases (balance_sheet, entity_profile), bare verbs (forget, subscribe), verb+noun (compare_entities, resolve_entity), and adjective+noun (historical_price, recent_alerts). No single pattern dominates, making it harder to guess tool names.

Tool Count2/5

55 tools is excessive for a server labeled 'Fmp'. The core financial data tools are perhaps 20-25, while the rest are unrelated: memory utilities, prediction market analyzers, web scraping, and meta-routing tools. This bloated set dilutes the server's purpose and burdens the agent with irrelevant options.

Completeness2/5

For the declared domain (FMP financials), the set covers the main statements but lacks tools like segment data, insider trades (listed as paid), or ownership details (also paid). Conversely, it includes many tools for prediction markets and general data retrieval that don't belong here, creating a mismatch between server name and actual capability.

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