list_jobsList the most recent remote jobs from RemoteOK (a popular, tech-heavy remote-work job board; keyless). Returns the newest postings (id, position, company, location, tags, salary range, date, url) without the long HTML description. Salaries are USD when present (0 = not disclosed).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max jobs to return (default 20, max 100). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds specifics: returns only recent postings with selected fields, no HTML description, and salary behavior (USD, 0=undisclosed).
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?
Two sentences: first states purpose and source, second details returned fields and salary. Front-loaded, no wasted words.
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 list tool with one optional parameter and no output schema, the description covers purpose, source, return fields, and salary nuances. No gaps.
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?
Schema describes the single optional 'limit' parameter with default and max. Description does not add beyond this, so baseline score of 3 for high schema coverage (100%) is appropriate.
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 lists the most recent remote jobs from RemoteOK, a specific source. It is distinct from sibling tools like search_jobs (filtered search) and get_job (single job).
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 implies usage for broad listing of recent jobs, but does not explicitly state when to use it versus alternatives like search_jobs. No when-not-to-use guidance is provided.
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.
Several tool clusters have fuzzy boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer questions through the same routing layer, while polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and bet_research all address prediction-market edges. Even with detailed descriptions, an agent can easily select the wrong variant.
Names are uniformly lowercase snake_case and many follow a verb_noun pattern (list_jobs, search_jobs, resolve_entity, validate_claim), but there are numerous noun-first and adjective-first exceptions (entity_profile, recent_alerts, pipeworx_trending, polymarket_arbitrage) plus bare verbs (remember, forget, recall, subscribe). The pattern is readable but not consistently applied.
34 tools is well above the well-scoped range, and the vast majority are not about the server's RemoteOK namesake. The set appears to merge several distinct domains (Pipeworx data research, Polymarket betting, RemoteOK jobs, memory utilities) into one oversized surface, making it feel more like a bundled platform than a focused server.
For the dominant Pipeworx/data-research theme, coverage is strong: question answering, grounded verification, entity profiles, comparisons, change feeds, discovery, memory, subscriptions, and citation-based research are all present. The RemoteOK job subset covers list/search/get without obvious dead ends. Minor gaps exist (no direct citation-URI fetcher, no job alert subscriptions), but agents can work around them.