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Glama

Fdic

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).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare readOnlyHint and idempotentHint. The description adds that mark_read:true flags events as read, a behavioral side effect beyond a simple read. It also details return fields (source, citation_uri, payload) and filter options, providing good context without 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 focused sentences: purpose, return fields, filter/mark_read behavior, and polling/alternative URL. No fluff, all sentences add value, front-loaded with essential info.

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 no output schema, the description adequately covers return format (source, citation_uri, payload) and key behaviors (filtering, mark_read, polling). Missing details on error conditions or authentication, but sufficient for a simple read tool with high schema coverage.

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 covers all 5 parameters with descriptions (100% coverage). The description adds a concrete filter example ('sec_8k') and clarifies mark_read behavior, but does not significantly extend schema meaning. Baseline 3 is appropriate.

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 pulls fired events from a subscription feed using the verb 'Pull' and specifies the resource as alerts/events. It distinguishes from siblings like list_subscriptions and recent_changes by focusing on event retrieval from a persisted feed.

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 implies usage for viewing recent alerts and mentions polling suitability and an alternative URL. It does not explicitly exclude other tools or provide when-not-to-use guidance, but the context is clear given sibling differences.

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

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer questions over the same underlying data catalog, and the five polymarket_* tools plus bet_research all analyze prediction-market opportunities. Tools like entity_profile, recent_changes, compare_entities, and resolve_entity also blur together for company research.

Naming Consistency2/5

Names are all snake_case but follow no consistent convention: some are bare verbs (forget, recall, remember, subscribe), some are noun phrases (fdic_failures, entity_profile, pipeworx_trending), and some are verb_noun (fdic_get_institution, generate_llms_txt, validate_claim). Even the fdic_* family mixes noun-only and verb_noun styles.

Tool Count2/5

At 36 tools this exceeds the 25-tool threshold for 'too many.' The count is inflated by redundant meta-tools (three ask_pipeworx variants, discover_tools, suggest_questions, multiple polymarket scanners) and unrelated purpose tools (generate_llms_txt, scan_dependency, ai_visibility_check) that do not belong in an FDIC-named server.

Completeness3/5

The universal ask_pipeworx router gives broad data coverage for almost any factual question, so core lookups are unlikely to dead-end. However, the FDIC-specific surface is thin (only five tools, missing branch/geography/history data), and the server's actual scope is so broad and mixed that no single domain is fully covered end-to-end.

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