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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

A4.7/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but description discloses that mark_read modifies state (flags events read), which slightly contradicts idempotency assumption. However, it accurately describes return payload fields and the alternative HTTP access method, adding value beyond annotations.

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?

Three sentences are efficient and front-loaded with core purpose. Every sentence adds value: main action, return fields, filtering, mark_read behavior, and alternative access method. No redundant information.

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?

No output schema, but description explains exactly what each returned event contains (source, citation_uri, payload). Covers filtering, mark_read, and alternative endpoint, providing all necessary context for an agent to use 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 baseline is 3. Description reinforces parameter meanings with concrete examples (e.g., 'sec_8k' for type, ISO timestamp for since) and explains the practical effect of mark_read, enhancing understanding beyond 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?

Clearly states the tool pulls fired events from subscription feed and returns recent alerts with specific fields (source, citation_uri, payload). Differentiates from sibling tools by focusing on recent alerts and mentioning mark_read functionality.

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 (polls work fine) and when the alternative HTTP endpoint is appropriate for scripts/dashboards. Also explains mark_read usage to control which alerts appear in subsequent calls.

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

A3.5/5.0
Disambiguation2/5

Several tools are near-duplicates: ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx, and multiple prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage) overlap in purpose. The Solana-specific tools are distinct, but the large non-Solana cluster creates real ambiguity.

Naming Consistency3/5

All tools use snake_case, but naming styles vary widely: get_/list_ verbs, ask_pipeworx family, polymarket_* cluster, and descriptive noun-style names like entity_profile, validate_claim, generate_llms_txt, scan_dependency. There is no single consistent verb_noun convention across the set.

Tool Count1/5

With 36 tools, the count is high, but the critical problem is scope mismatch: a server named Solscan has only 5 Solana-related tools, while 31 are unrelated data/research/prediction-market utilities. This makes the tool count inappropriate for the apparent purpose.

Completeness2/5

As a Solana explorer, the set covers only account details, token holdings, token metadata, transactions, and transfers; major gaps include blocks, token price/history, NFTs, programs/staking, and more comprehensive transfer history. For the broader data-research theme, coverage is broad but scattered and lacks a single coherent domain.