Silicon Analysts

get_market_pulse

Read-onlyIdempotent

Returns curated supply-chain headlines with trend direction (up/down/neutral), source attribution, and impact analysis. Categories: logic, memory, packaging, connectivity, power, geopolitics. Defaults to all categories, all trends, no limit.

USE THIS for: "what's happening in HBM this quarter?", "any geopolitical moves affecting TSMC?", recent supply/demand inflections.

DO NOT USE for: structured pricing data (use get_wafer_pricing, get_hbm_market_data); published cost of a specific chip (use get_accelerator_costs).

Per-item dates are formatted strings (e.g., "Jan 2026") — not ISO 8601. Cache: 5 minutes server-side. Returns empty array if all items filtered out.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`trend`	No
`category`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedMay 31, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already indicate read-only/idempotent behavior. The description adds valuable non-obvious details: default filters (all categories/trends/no limit), date format caveat (not ISO 8601), server-side cache of 5 minutes, and empty-array behavior when filters match nothing. No contradiction with annotations.

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 well-structured with a clear first line stating the primary purpose, followed by usage guidance, exclusions, and caveats. Every sentence adds value, and the USE THIS/DO NOT USE sections make it scannable without excess verbosity.

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?

For a list-returning tool with no output schema, the description is comprehensive. It explains what items contain (headline, trend, source, impact), available filters, default behavior, date formatting, cache behavior, and edge case (empty array). This is sufficient for an agent to invoke the tool correctly and interpret results.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It mentions categories and trend direction in the main sentence and explains defaults ('Defaults to all categories, all trends, no limit'). However, it does not explicitly explain the 'limit' parameter semantics (e.g., maximum number of items) or clarify whether category/trend accept multiple values (schema shows single enum). Partial compensation but not complete.

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 returns curated supply-chain headlines with trend direction, source attribution, and impact analysis. It specifies categories (logic, memory, packaging, etc.) and defaults, making the scope distinct from siblings. The explicit 'DO NOT USE' section further differentiates it from pricing and cost tools.

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

Usage Guidelines5/5

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

Provides explicit USE THIS examples ('what's happening in HBM this quarter?') and DO NOT USE cases with named alternatives (get_wafer_pricing, get_hbm_market_data, get_accelerator_costs). This gives the agent clear decision criteria for tool selection.

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

A4.4/5.0

Disambiguation3/5

Several tools overlap in domain and purpose, such as get_market_pulse vs get_market_intelligence and get_wafer_pricing vs get_foundry_economics. The detailed USE/DO NOT USE sections help, but the tool names alone do not always make the distinction obvious, requiring careful reading to avoid misselection.

Naming Consistency4/5

18 of 20 tools follow a consistent get_<noun> pattern, with calculate_chip_cost and estimate_lead_time as minor deviations. No chaotic mixing of camelCase or inconsistent verb styles; the overall scheme is predictable and readable.

Tool Count4/5

20 tools is slightly above the ideal 3-15 range but reasonable for the server's broad scope covering cost modeling, capacity, allocation, HBM, policy, and market intelligence. Each tool has a distinct niche, though a few could potentially be consolidated.

Completeness4/5

The server provides comprehensive coverage of semiconductor cost estimation, market data, fab capacity, allocation, HBM qualification, and policy timelines. Minor gaps exist (e.g., no dedicated memory pricing tool or general search), but these are covered through get_market_dataset and other tools; there are no critical missing functions for the stated domain.

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