Skip to main content
Glama

crashtestyourstrategy

by io.github.fnobbe

Find similar regime via behavioural descriptors

find_similar_regime
Read-onlyIdempotent

Nearest-neighbour retrieval over the cached regime catalogue. Provide EITHER a reference_profile_hint (use that bundle's median descriptors as target) OR a descriptor_target dict (partial spec, missing dimensions are ignored — only the provided ones contribute to distance). Optional asset_filter restricts to one asset. Returns top_n matches with similarity_score (0..1), euclidean distance in z-score space, and per-descriptor signed deltas so the agent can see WHY a regime matched. Read ontology://regime-descriptors for the descriptor definitions, and regimes://descriptors for the full catalogue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoNumber of nearest regimes to return.
asset_filterNoRestrict matches to one asset (e.g. 'SPY', 'BTC').
descriptor_targetNoPartial target spec {descriptor_name: value}; only the provided dimensions contribute to the distance. Definitions: ontology://regime-descriptors.
reference_profile_hintNoUse this catalogue bundle's median descriptors as the search target (mutually exclusive with descriptor_target).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral details: missing dimensions in descriptor_target are ignored, distance is computed in z-score space, and per-descriptor signed deltas are returned so the agent can understand the match. It also points to ontology and catalogue references, going well beyond the 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 compact (two sentences) yet covers the essential input modes, output fields, and references. It is front-loaded with the main purpose and every clause adds value. No redundant or extraneous information.

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?

Given the tool's moderate complexity (4 optional parameters, output schema present, annotations provided), the description is thorough. It covers the two mutually exclusive inputs, the optional filter, the return value (top_n matches with similarity and deltas), and where to get further definitions. It does not detail error cases for missing both inputs, but with an output schema and the description's explicit 'Provide EITHER' phrasing, the context is sufficiently complete.

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 input schema already provides descriptions for all four parameters (100% coverage), so the baseline is 3. The description adds extra semantic clarity, especially for descriptor_target: 'missing dimensions are ignored — only the provided ones contribute to distance.' It also reinforces the mutual exclusivity of the two input modes, which is present in schema but emphasized in context.

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 a specific verb+resource: 'Nearest-neighbour retrieval over the cached regime catalogue.' It clearly distinguishes this from sibling tools like describe_regime or market_regime_map by focusing on similarity search. The two input modes and the output (similarity_score, distance, deltas) are precisely stated.

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?

The description clearly states how to use the tool: provide EITHER a reference_profile_hint OR a descriptor_target, with an optional asset_filter. It does not explicitly name alternatives or exclusion conditions beyond what is inherent, but the usage context is clear. No explicit 'when not to use' guidance is given, which keeps it from a 5.

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

All crashtestyourstrategy toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation4/5

Most tools target distinct resources/actions (regime introspection vs. portfolio stress vs. thesis management), but a few names like run_stress_test vs. portfolio_stress_test could cause confusion. Descriptions help clarify boundaries, but there is enough overlap to mark one point off.

Naming Consistency3/5

Names are mostly snake_case but mix verb_noun (get_dossier, run_stress_test) with noun phrases (factor_decomposition, market_regime_map). The verb style is inconsistent (get/list/run/describe/submit/challenge), though the pattern is readable. This falls between predictable and chaotic.

Tool Count4/5

16 tools is slightly above the typical 3-15 range, but the domain is broad (regime analysis, portfolio stress testing, strategy evaluation, feedback). Most tools are distinct and necessary; only a couple could be merged without loss of functionality.

Completeness4/5

The surface covers core workflows: discovering theses, stress-testing portfolios, analyzing regimes, evaluating strategy robustness, and collecting feedback. Minor gaps exist (e.g., no custom strategy builder, challenge_strategy only supports buy-and-hold), but these are explicitly noted as future work.

Resources