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signalpulse-mcp

by com.theaslangroupllc.signalpulse

signal_macro

Macro — Polymarket econ-threshold ladder scan (CPI inflation / unemployment / 10y yield): realized official-print floor (BLS + Treasury) + trend-implied remaining-prints band vs every bucket book, best divergence; ?family=cpi_yoy|unrate|us10y narrows [PAID — signal credit or x402 USDC. Cost: 1 signal credit ($1.70-$2.49/credit by pack size). Uncredentialed calls return the 402 payment envelope; set X-API-KEY on the MCP connection or pay x402 out-of-band at GET /api/signal/macro.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description fully carries the behavioral burden. It discloses payment requirements ('1 signal credit ($1.70-$2.49/credit by pack size)'), auth options ('set X-API-KEY on the MCP connection or pay x402 out-of-band'), the uncredentialed 402 response, and the internal scan logic. This is substantial, honest behavioral detail.

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

Conciseness3/5

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

The description is a single dense run-on sentence with semicolons, parentheses, and a large bracketed payment block. It is information-rich but poorly structured for quick parsing; splitting into concise sentences would improve readability without losing content.

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

Completeness4/5

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

Given no output schema and no annotations, the description covers core purpose, a key parameter, and essential payment/auth behaviors. It does not describe the response shape, but the schema's suggestion to consult 'instruments' for parameter docs mitigates this gap.

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 schema declares 0 formal parameters and only generic additionalProperties, but the description documents a concrete '?family=cpi_yoy|unrate|us10y' parameter with its narrowing effect. This exceeds the baseline for 0-param schemas and adds real selection/invocation value.

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 opens with 'Macro — Polymarket econ-threshold ladder scan (CPI inflation / unemployment / 10y yield)' and explains the comparison logic (realized floor + trend-implied band vs every bucket book), making the tool's function explicit and clearly differentiating it from sibling scan_* and signal_* tools.

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?

No explicit when-to-use or alternative guidance is provided. The only usage hint is the optional '?family=cpi_yoy|unrate|us10y' narrowing parameter, plus a pointer to the 'instruments' tool in the schema description. The macro-econ scope implies context but does not state a decision rule.

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

B3.1/5.0
Disambiguation2/5

There is significant overlap between scan_* and signal_* tools for the same underlying asset classes, e.g. scan_futures vs signal_futures, scan_racing vs signal_racing, and scan_predmarket vs signal_polymarket. Broader catch-alls like analysis, scan_ask, backtest, and signal_generate also blur the boundary, forcing an agent to parse long pricing details before knowing which tool actually applies.

Naming Consistency4/5

The overwhelming majority of tools follow a clear `scan_` or `signal_` snake_case prefix, which makes the product families easy to recognize. A small set of standalone unprefixed tools — analysis, backtest, instruments, leaderboard, quote, track_record — breaks the pattern, but the overall scheme is still consistent enough to infer.

Tool Count2/5

47 tools is far beyond the practical range for an agent to reason about, even though the server's domain is broad and heavily segmented. Many specialist endpoints could be consolidated under fewer catch-all scanners and signals, but the exposed surface instead forces a large tool-selection decision on every request.

Completeness4/5

The tool surface covers discovery, cost preview, sample analysis, public track records, leaderboards, broad market scanning, asset-class-specific scanning, sports and event signals, and prediction-market verticals. There are minor gaps in explicit account/credit management and some redundant paths, but for a signal/research service the workflow is largely complete.

Resources