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LiquiLens — the Failure Radar

Historical diagnostic: one Indian case replay

evidence_institution
Read-onlyIdempotent

Read one Indian institution's complete construction-PIT crisis replay from the 48-institution diagnostic: the scored quarterly trajectory, the sourced dossier rows behind each score, first-alert bookkeeping (when each lens first fired relative to the failure), and the plain verdict line — hit, miss or false alarm. Call evidence_india first to list the replayed institutions and their slugs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYeskebab-case slug of a replayed institution, e.g. 'dhfl' or 'global-trust-bank'

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, covering safety and idempotence. The description adds meaningful context about what the replay includes, such as 'first-alert bookkeeping' and 'plain verdict line,' going beyond a bare read-only statement and giving the agent a detailed expectation of the returned content.

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 exactly two sentences, front-loaded with the main action 'Read' and immediately enumerating the data items. The second sentence is a clear directive for the prerequisite step. Every word earns its place; no fluff or repetition.

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 single-parameter read-only lookup, the description is complete: it names the exact resource, lists all relevant data components, and explains the prerequisite relationship to evidence_india. No output schema exists, but the description sufficiently specifies what will be returned.

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?

The schema already documents the single 'slug' parameter with a description and example, so baseline is 3. The description adds value by instructing the agent to obtain the slug from evidence_india, providing a concrete lookup path that the schema alone doesn't convey.

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 states a specific verb ('Read') and resource ('one Indian institution's complete construction-PIT crisis replay'), enumerating the contents (scored quarterly trajectory, dossier rows, alert bookkeeping, verdict line). It clearly distinguishes from sibling evidence_india by explicitly pointing to it as the list-first step.

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 explicitly says 'Call evidence_india first to list the replayed institutions and their slugs,' giving a concrete prerequisite and alternative. The India-specific scope and 'one institution' nature further clarify when this tool is appropriate versus siblings like evidence_europe or evidence_markets.

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
Disambiguation5/5

Each tool targets a distinct resource, sector, or function: sector-specific boards (corporate, household, crypto, stablecoin, failure radar), evidence details by region, verification, search, and review packet generation. Descriptions explicitly delineate boundaries, leaving no ambiguity about which tool to select.

Naming Consistency3/5

There are recognizable families (e.g., *_board for dashboards, evidence_* for validation records), but the set mixes conventions: noun-phrase boards, verb-first tools like universe_search and verify_published_record, and standalone nouns like forward_odds. This is readable but not uniform.

Tool Count4/5

17 tools is slightly above the ideal 3-15 range, but each tool has a distinct purpose and no redundancy. The count feels justified given the breadth of domains (India, US, Europe, crypto, stablecoins) and functions (monitoring, validation, verification, review).

Completeness5/5

The set covers the full workflow: universe_search for discovery, sector boards for monitoring, failure_radar_institution for deep dives, evidence_* for validation, forward_odds for probability context, verify_published_record for integrity, and institution_review_packet for human review. No obvious gaps or dead ends for the stated failure-radar domain.

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