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Alion: company, startup and market intelligence

Watch a search for new results

watch_search

Save a search of jobs, companies or people and come back for what is new: kind is jobs, companies or people, filters are the arguments of search_jobs, search_companies or search_people (e.g. {"role":"Backend","country":"DE","work_mode":"remote"}). Answers the first page now (newest first, compact) and a watch_id; check_watch with it later returns only the rows that appeared since. Up to 20 watches per agent (an account, a wallet, or a network and client name). Use it for a job hunt, a hiring pipeline or a market you follow. Free. Docs: https://alion.io/developers/docs

Input Schema

NameRequiredDescriptionDefault
kindYes
nameNoA short label, e.g. "Remote Go roles in EU".
filtersYesThe search arguments to follow (cursor and limit are ignored).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond annotations by disclosing that the first page is returned immediately (newest first, compact), that a `watch_id` is issued for later diffing, and that there is a hard quota of 20 watches per agent with the account/wallet/network-client identity model spelled out. Annotations (readOnlyHint=false, idempotentHint=false, destructiveHint=false) are consistent with a non-destructive create-with-quota operation, and the description adds the cost ('Free') and docs link.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core value proposition (save and come back for what's new) and dense with useful detail; almost every clause carries information. It is a single unbroken block with stacked parentheticals, which slightly hurts scanability.

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?

With 3 params, a nested object, no output schema and no annotation for return shape, the description still tells the agent what comes back (first page now, compact, newest first, plus watch_id), how to consume it later, and the quota ceiling. Nothing essential for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67% and the schema leaves `filters` as an opaque object, but the description supplies an inline example filter set and specifies that its keys are the arguments of the corresponding search_* tool, with cursor and limit ignored. That is meaning the schema does not carry, so it more than compensates for the coverage gap.

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?

States a specific verb and resource — save a search over jobs/companies/people and retrieve what is new — and immediately ties the filters to the `search_jobs`/`search_companies`/`search_people` siblings, so the agent knows this is a persisted wrapper, not a plain search. The pairing with `check_watch` completes the picture of what the tool is for.

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?

Gives concrete use cases ('a job hunt, a hiring pipeline or a market you follow') and explicitly routes follow-up retrieval to `check_watch`, which is the key alternative-facing guidance. It stops short of an explicit exclusion (e.g. 'use search_jobs directly for a one-off lookup'), so the when-not is only implied.

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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