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bitcoin-signals

by com.coinbucha

Bitcoin hiring velocity

get_hiring_signal
Read-onlyIdempotent

Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards. Returns { as_of, companies[], note, why, disclaimer }; each company carries company, ticker, category, ats, careers_url, open_roles, open_roles_30d_ago, open_roles_90d_ago and the derived delta_30d, delta_90d and pct_30d. Example: {"company": "coinbase"} for one employer, or {} for every employer tracked. When a company filter matches no tracked employer the response adds coverage_note and tracked_count, saying that the name is outside the tracked set — a limit of coverage, not a finding about whether that company is hiring. Information, not financial advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyNoCase-insensitive company filter

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent, but the description adds substantial behavioral detail: data source ('live ATS boards'), exact response structure, derived fields (delta_30d, pct_30d), and the coverage_note/tracked_count behavior for unmatched companies. This enriches the agent's understanding beyond the basic safety hints.

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?

The description is dense but every sentence serves a purpose: purpose, return format, example, edge case, and disclaimer. It front-loads the core function and organizes information logically, with no redundancy or filler.

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?

Given the lack of an output schema, the description thoroughly documents the response object and key fields. It covers usage examples, edge-case behavior, and includes a disclaimer about non-financial advice, making the tool's behavior and limitations clear.

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?

The single optional 'company' parameter is described with usage examples and response implications: empty object returns all tracked employers, and a non-matching filter produces a coverage_note explaining the name is outside the tracked set. This adds meaning far beyond the schema's 'Case-insensitive company filter'.

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 reports 'Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards.' This is a specific verb+resource combination that distinguishes it from sibling tools measuring ETF flows, network signals, or sovereign reserves. The title 'Bitcoin hiring velocity' reinforces the purpose.

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 provides clear usage context through examples: 'Example: {"company": "coinbase"} for one employer, or {} for every employer tracked.' It also explains behavior for unmatched filters. While it doesn't explicitly mention alternatives, the narrow scope and examples make when to use it evident.

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

A4.3/5.0
Disambiguation4/5

Tools target distinct data sources: ETF flows, hiring, network hashrate, sovereign reserves, treasury holdings, and a cross-signal scan. get_daily_brew and scan_signals both summarize signals but differ in format (digest vs. ranked list), creating mild potential for confusion. Overall, descriptions clearly differentiate purposes.

Naming Consistency4/5

Six of seven tools follow a consistent get_<resource> pattern (e.g., get_etf_flows, get_treasury_holdings). scan_signals breaks the pattern with a different verb, and get_daily_brew uses a non-resource name, but the deviation is minor and the naming remains intuitive.

Tool Count5/5

With 7 tools, the set is well-scoped for a Bitcoin signals server. Each tool covers a distinct signal category without excess or redundancy, making the count appropriate for the domain.

Completeness4/5

The tool surface covers a broad range of leading Bitcoin indicators (network, institutional flows, corporate and sovereign holdings, hiring, and a composite scan). Potential minor gaps exist (e.g., sentiment or derivatives data), but the core signal set appears reasonably complete for the stated purpose.

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