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Htmltext

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

A4.4/5.0
Behavior4/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint false. The description adds behavioral context: mark_read sets events as read, affecting subsequent calls. No contradiction found.

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?

Description is two sentences, front-loaded with core purpose, then adds details. Every sentence contributes meaning—no redundancy or fluff.

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?

No output schema, but description lists returned fields. Parameters are fully documented. For a read-only list tool with 5 optional parameters, the description provides sufficient context for effective use.

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. The description enhances parameter understanding: explains mark_read effect (flag returned events read), gives example values for type ('sec_8k'), and implies ISO format for since. Adds value beyond schema.

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, specifies returned fields (source, citation_uri, raw payload), and mentions filtering options. It distinguishes itself from siblings like 'list_subscriptions' which manages subscriptions, not alerts.

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 says 'Polls work fine' and provides an alternative REST endpoint, indicating when to use this tool versus scripts/dashboards. It lacks explicit when-not-to-use instructions but gives clear context.

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

A4.1/5.0
Disambiguation3/5

Several tools form overlapping clusters (ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded, the five polymarket_* tools, and discover_tools vs suggest_questions) that could cause misselection on first glance. The detailed descriptions mostly clarify the boundaries, but the overlaps are real and require careful reading.

Naming Consistency4/5

The naming is overwhelmingly snake_case with a verb_noun pattern (ask_, extract_, generate_, list_, resolve_, subscribe), which is predictable. A few noun-style or special-form names (entity_profile, html_to_text, recent_changes, polymarket_edges) break the pattern, but these are minor deviations.

Tool Count2/5

At 34 tools the surface is heavy, especially for a server named 'Htmltext' where only 4 of 34 tools relate to HTML. Even accounting for the broad data/research domain, the set includes several redundant research and Polymarket helpers that push it past a well-scoped count.

Completeness4/5

The major subdomains are well covered: HTML extraction, entity/data research, prediction-market analysis, memory, and subscriptions all have the core operations needed with no obvious dead ends. Some niches are shallow (HTML lacks a general fetch/render tool; scan_dependency is a one-off), but agents can work around these gaps.

Resources