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JYOTINT Sealed Forecasts

by com.jyotishintelligence

neural_search

SEMANTIC + ASSOCIATIVE search over the public sealed record and the published site corpus — the JYOTINT public brain (a neural associative memory: frozen deep encoder → Hopfield pattern completion → spreading activation over typed synapses → k-winners-take-all). Finds calls by MEANING, not keywords ('upper-stage anomalies' finds the calls that describe one without those words) and returns the RELATED subgraph, not just isolated hits. Retrieval-only and non-generative: every result is VERBATIM sealed/published text with public provenance (source URL, SHA-256 seal hash, frozen grade) plus an explainable why/activation path and Hopfield convergence info. Prefer this over search_sealed_forecasts for fuzzy/conceptual queries; the REST twin is GET /brain?q=…

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoMax results, 1–12 (default 6).
queryYesNatural-language query (e.g. 'what did the record say before the Crocus attack', 'upper stage anomaly calls').

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden. It discloses retrieval-only and non-generative behavior, verbatim result provenance (source URL, SHA-256 seal hash, frozen grade), explainable activation path, and Hopfield convergence information, offering substantial behavioral context beyond basic functionality.

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 front-loaded with the main purpose and is structured logically, but it includes some technical details (e.g., Hopfield stages) that are informative yet slightly verbose. Overall it earns its place with meaningful content, though it could be tightened.

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?

Despite lacking an output schema, the description fully explains what the tool returns: a related subgraph, verbatim text with provenance, activation path, and Hopfield convergence info. It also mentions the REST twin, making it complete for an agent to understand expected outputs and usage context.

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?

The input schema describes both parameters (query and k) with examples and constraints, achieving 100% coverage. The description does not add extra parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 explicitly states 'SEMANTIC + ASSOCIATIVE search over the public sealed record and the published site corpus' and explains the mechanism, clearly distinguishing it from sibling tools by indicating a preference over search_sealed_forecasts for fuzzy/conceptual queries.

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 provides explicit usage guidance by stating 'Prefer this over search_sealed_forecasts for fuzzy/conceptual queries' and explains that it finds by meaning rather than keywords, implying when not to use it (exact keyword queries).

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

All JYOTINT Sealed Forecasts toolsInspect
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TDQS

A3.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (fetch one forecast vs. list open calls vs. search), but neural_search and search_sealed_forecasts both retrieve from the same corpus, and ask_the_record overlaps slightly with neural_search for site-copy questions. Descriptions mitigate ambiguity, but a few boundaries require careful reading.

Naming Consistency4/5

The dominant pattern is get_<noun> (get_advisory, get_map, get_luck_test), with list_open_calls, search_sealed_forecasts, ask_the_record, and neural_search as deviations. All names are lowercase snake_case and readable, but the verb prefixes are not perfectly uniform.

Tool Count5/5

With 13 tools, the server is well-scoped for a specialized sealed-forecast corpus. Each tool addresses a distinct analytical or retrieval need, and the count fits comfortably in the ideal range without feeling bloated or thin.

Completeness5/5

The tool surface covers the full lifecycle of interacting with the corpus: search, retrieve, list, inspect stats, verify integrity, regrade, visualize, and ask questions. The append-only nature means no update/delete tools are needed, so the set is complete for its stated purpose.

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