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Glama

Outlook Contacts

by io.github.pipeworx-io

Pipeworx Trending

pipeworx_trending
Read-onlyIdempotent

What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNo24h (default) | 7d | 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true. The description adds valuable behavioral context: 'Self-aggregating signal — derived from CF analytics-engine, no PII' and 'Cached 5min-1h depending on window.' This goes beyond annotations.

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?

Description is well-structured with clear sections and bullet-like use cases. It is front-loaded but slightly verbose; each sentence adds value but could be more concise.

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 simple tool with one optional parameter and no output schema, the description fully covers what is returned (top tools, packs, volume, window), caching, and derivation. No gaps apparent.

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?

Schema coverage is 100% and the description adds meaning: explains that shorter windows surface hot trends and longer windows show steady-state demand. This extends the enum values.

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 top tools, packs, and call volume over a window. It uses a specific verb ('Returns') and resource ('top tools, top packs, total call volume'), and distinguishes from sibling tools like discover_tools by focusing on trending usage from AI agents.

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?

Explicitly lists three use cases (discovering hot data sources, confirming canonical tools, aligning use cases). However, it does not provide exclusions or alternatives, which would improve guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Outlook Contacts toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tools are near-duplicates by name and function, notably ask_pipeworx vs ask_pipeworx_beta, and the dense Polymarket family (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). Long descriptions help, but an agent cannot reliably pick between these without reading closely.

Naming Consistency4/5

Almost all names are lowercase_snake_case and mostly verb-leading (discover_tools, resolve_entity, unsubscribe), but there are noun-first exceptions (entity_profile, recent_changes, pipework_trending) and several phrasal or compound forms. This is a minor deviation from a clean verb_noun pattern rather than a chaotic mix.

Tool Count2/5

31 tools is over the heavy threshold, and the set feels bloated: multiple query routers, a half-dozen overlapping Polymarket tools, and two AI-visibility probes that could be merged. The count is especially hard to justify for a server named Tools 'OutLook Contacts', since none are contact management.

Completeness1/5

For the server's stated domain, Outlook Contacts, there are zero tools in that domain — no create contact, no list contacts, no update, no delete, no folders or mailboxes. Even though the actual Pipework toolkit is broad for its own domain, this set fails its declared intend domain entirely.

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