encode_htmlEncode text to HTML entities. mode "basic" (default) escapes only & < > " '; mode "extended" also converts every non-ASCII character to a numeric entity. Keyless, offline.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | "basic" (default) or "extended". | |
| text | Yes | The text to encode. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral specifics beyond annotations: the exact characters escaped in each mode and the operational trait 'Keyless, offline'. This gives the agent a clear and complete picture of what the tool does.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. The first sentence immediately states the action, and the second sentence efficiently covers the modes. It is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, side-effect-free utility with a complete schema, strong annotations, and no output schema, the description covers the core functionality, mode differences, and operational constraints (keyless, offline). It is fully sufficient 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.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes both parameters with 100% coverage, but the description enriches them further by explaining the 'basic' vs 'extended' modes and listing the exact characters each handles. This adds meaning that the schema alone does not convey.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Encode text to HTML entities'. It distinguishes itself from the sibling decode_html by focusing on encoding, and further distinguishes its two modes by explicating what each does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context by noting 'Keyless, offline' and explains the choice between basic and extended modes, which helps decide how to invoke the tool. However, it does not explicitly compare with alternatives like decode_html or mention when not to use this tool, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools overlap heavily: ask_pipeworx, ask_pipeworx_beta (currently identical), and ask_pipeworx_grounded share the same routing core, while bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk all target prediction-market edge detection. The descriptions are detailed, but an agent must read a lot of nuance to avoid selecting the wrong tool.
All names are lowercase snake_case and readable, but the convention is mixed: verb_noun names like encode_html and resolve_entity sit alongside bare verbs like remember and forget, and noun-phrase names like entity_profile, recent_changes, and polymarket_fill_risk. The ask_pipeworx_* and polymarket_* families are internally consistent, but there is no single predictable pattern across the whole set.
At 33 tools this exceeds the 25+ threshold for a heavy set. The bloat is especially noticeable because the server is named Htmlentities yet only encode_html and decode_html relate to that purpose; the rest are unrelated Pipeworx research, prediction-market, memory, and subscription utilities.
The Pipeworx surface is broadly complete: ask/grounded/deep_research/discover/suggest cover data access, entity_profile/compare_entities/recent_changes/validate_claim cover entity workflows, and subscriptions and memory have create/list/delete lifecycles. Minor gaps such as no update operation for subscriptions or memories are workable, and encode/decode fully covers the literal Htmlentities purpose.