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agentery

by com.agentery

research_capability

START HERE for provider procurement. ONE call turns a task into: (1) its live MARKET — the semantic neighbourhood of the closest-matching providers, found purely by text-embedding nearness (NO fixed category), with the relevance floor and how many providers cleared it; (2) current pricing context — comparable price range and median with mean, stdev and n, plus provider/priced counts; and (3) a ready-to-compare provider shortlist — each with observed price, market_position (below/in-line/above market), integration status, match score, and handles collected in compare_ready. Retrieval is 100% nearest-neighbour by text embedding: providers are matched on what they actually DO, never on an assigned label. REUSES the canonical pricing/search engines (no new pricing logic). Also returns suggested_alternatives (cheaper or stronger options) and a result_fingerprint (+ cached) so repeat calls are cheap. It does NOT run the comparison — pass compare_ready to compare_providers once you have finalists. Use the lower-level tools (find_market, market_report, price_benchmark, search_providers) for finer control. Aliases: task also accepts query / q.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoShortlist ordering. Default 'match'.
taskYesRequired — the natural-language capability/task, e.g. 'reconcile supplier invoices' or 'litigation-analysis provider'. Aliases: query, q.
limitNoShortlist size (1-12, default 5).
buyer_tierNoOptional buyer tier to price against ('team' = Team/SME).
integrationsNoOptional required integrations, e.g. ["zendesk","slack"] — soft preference; integration status is reported per provider.
provider_typeNoPreferred delivery type. 'auto' (default) infers from the task; note 'AI agent' phrasing is treated as generic (neutral), not an agent-only filter. When a type is explicit (mcp/api/agent) matching providers are SOFT-RANKED to the top and the rest are kept as clearly-labelled cross_type_alternative entries — never hard-filtered (no zero-result cliff), and the functional match is never changed. Every provider is labelled with provider_type (public values: agent | mcp | api | unknown) + type_match_score; provider_type{type_rank_boost_applied, boosted_provider_type, result_counts_by_type} is returned.
response_modeNo'summary' (default) or 'full' (adds tier cohorts, coverage and raw results).
max_monthly_usdNoOptional budget ceiling in USD/month — filters the shortlist and drives suggested_alternatives.

TDQS

A4.8/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden, and it delivers: it discloses the 100% nearest-neighbour retrieval mechanism, the absence of fixed categories, reuse of canonical pricing/search engines, the soft-ranking/no-hard-filter behavior for provider_type, and that repeat calls are cheap via result_fingerprint/cached. It also explicitly states what the tool does NOT do (run the comparison), preventing misuse.

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-loaded with 'START HERE', and every sentence conveys a distinct fact about behavior, outputs, or alternatives. It could be slightly better structured with bullets or more compact phrasing, but given the complexity of the tool, the length is justified.

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?

This is a complex orchestrator tool with 8 parameters and no output schema, so the description carries the burden of explaining return values and behavior. It comprehensively enumerates the three main output groups, additional fields (suggested_alternatives, result_fingerprint, cached), provider labels, and relationships to sibling tools. An agent has enough context to invoke and interpret the result without additional lookups.

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 description coverage is 100%, so the baseline is 3, but the description adds meaningful semantics beyond the schema: it explains that provider_type matching is soft-ranked with cross_type_alternative entries and no zero-result cliff, that max_monthly_usd drives suggested_alternatives, and that task supports aliases. These enrich the schema without replacing it.

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 'START HERE for provider procurement' and specifies a concrete verb+resource: one call produces market, pricing context, and a provider shortlist. It clearly distinguishes itself from siblings by explicitly stating it does not run the comparison and directing the agent to compare_providers and lower-level tools like find_market and price_benchmark.

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?

The description gives explicit when-to-use guidance ('START HERE'), what to do after use ('pass compare_ready to compare_providers once you have finalists'), and explicitly names alternative lower-level tools for finer control. This makes the selection decision clear for an agent.

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

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but a few pairs could cause confusion: get_provider vs get_provider_profile overlap in scope (one is a card, the other a full profile), and research_capability explicitly bundles find_niche, niche_report, price_benchmark, and search_providers, creating layered redundancy. However, the detailed descriptions clearly differentiate the entry-point tools from the lower-level ones.

Naming Consistency4/5

The majority follow a verb_noun pattern (create_, delete_, get_, search_, suggest_, etc.), but a few tools use bare noun phrases (demand_signals, market_gaps, niche_report, price_benchmark) rather than imperative or get_ prefixes. This is a minor inconsistency that doesn't harm readability.

Tool Count4/5

At 19 tools, the set is slightly above the ideal 3-15 range but each tool serves a distinct, justified function within the market-intelligence and provider-directory domain. The count feels appropriate for the breadth of features (search, research, comparison, pricing, indexes, benchmarks, and feedback).

Completeness5/5

The tool surface is very comprehensive: full CRUD for custom benchmarks, multiple discovery paths (search, research, gaps, demand signals), pricing and index tools, profile/detail tools, comparison and alternatives, plus outcome reporting. There are no obvious dead ends or missing critical operations for the stated purpose.

Resources