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HSH Data-on-Demand

by io.github.hshintelligence
OverviewDiscussionsAdmin

hsh-hiring-signal

Multi-signal alt-data intel for investment research. Combines up to six independent free signals into one call: (1) HIRING posture across Greenhouse + Lever + Ashby job boards (gtm_expansion / product_build / balanced_growth / hiring_freeze from department mix); (2) INSIDER activity from SEC Form 4 filings (last 90 days); (3) GITHUB engineering velocity (stars, push recency); (4) WIKIPEDIA public-interest trend; (5) APP STORE top-free ranking presence; (6) HACKER NEWS mention velocity. Operational and behavioural readings of the company: no price prediction is made or claimed. Pass whichever identifiers you have. Pay per call via x402 (USDC on Base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hnNoHacker News search term for buzz signal.
wikiNoWikipedia article title for interest signal (e.g. Coinbase).
ashbyNoAshby slug (e.g. ramp).
leverNoLever slug (e.g. spotify).
githubNoGitHub owner/repo for engineering-velocity signal (e.g. stripe/stripe-node).
tickerNoStock ticker for SEC insider signal (e.g. COIN, AAPL).
companyYesCompany display name.
ios_appNoiOS app name to check top-free ranking (e.g. Cash App).
greenhouseNoGreenhouse board token (e.g. stripe, coinbase).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed9 schema fields changed
    • addedInput schema / properties / ashby
      Added value: +{
+  "description": "Ashby slug (e.g. ramp).",
+  "type": "string"
+}
    • changedInput schema / properties / company / description
      Previous value: -"Company job-board token (e.g. stripe, coinbase) or supported ticker (e.g. COIN, SNOW)."New value: +"Company display name."
    • addedInput schema / properties / github
      Added value: +{
+  "description": "GitHub owner/repo for engineering-velocity signal (e.g. stripe/stripe-node).",
+  "type": "string"
+}
    • addedInput schema / properties / greenhouse
      Added value: +{
+  "description": "Greenhouse board token (e.g. stripe, coinbase).",
+  "type": "string"
+}
    • addedInput schema / properties / hn
      Added value: +{
+  "description": "Hacker News search term for buzz signal.",
+  "type": "string"
+}
    • addedInput schema / properties / ios_app
      Added value: +{
+  "description": "iOS app name to check top-free ranking (e.g. Cash App).",
+  "type": "string"
+}
    • addedInput schema / properties / lever
      Added value: +{
+  "description": "Lever slug (e.g. spotify).",
+  "type": "string"
+}
    • addedInput schema / properties / ticker
      Added value: +{
+  "description": "Stock ticker for SEC insider signal (e.g. COIN, AAPL).",
+  "type": "string"
+}
    • addedInput schema / properties / wiki
      Added value: +{
+  "description": "Wikipedia article title for interest signal (e.g. Coinbase).",
+  "type": "string"
+}
  2. Added

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It discloses that the tool aggregates six signals, states the pay-per-call cost via x402, and explicitly disclaims price prediction. It does not mention rate limits or error handling, but the disclosed behaviors are material for an agent deciding whether to call the tool.

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?

The description is long but information-dense, front-loading the purpose and then enumerating the six signals in a numbered list. Every clause either defines a signal, scopes the output, or states payment terms; there is no filler. It is appropriately structured for an agent to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 9 parameters and no output schema, the description must compensate for missing return-type information. It explains input identifiers and gives a high-level 'operational and behavioural readings' summary, but does not describe the output structure, scale, or how the six signals combine into a final result. An agent can invoke correctly but may be uncertain about the expected response.

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?

Although the input schema already gives 100% param coverage with examples, the description adds semantic grouping: greenhouse/lever/ashby map to hiring posture, ticker to insider activity, github to engineering velocity, wiki/hn/ios_app to the remaining signals. This helps an agent understand how to combine parameters meaningfully, adding value beyond the 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 a specific verb and resource: it combines six independent free signals into one call, listing all six sources (hiring posture, insider activity, GitHub, Wikipedia, App Store, Hacker News). This distinguishes it from sibling tools like hsh-company-intelligence or hsh-crypto-intel, which focus on different data types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context ('alt-data intel for investment research') and a negative boundary ('no price prediction is made or claimed'), which implies appropriate use cases. However, it does not explicitly compare itself to sibling alternatives nor state when an agent should prefer this tool over a single-signal tool, leaving selection partially to inference.

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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