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crashtestyourstrategy

by io.github.fnobbe

Submit structured feedback

submit_feedback

Persist structured improvement feedback about a previous tool response. Provide your agent identity, the request_id you are commenting on, and one or more feedback items each carrying category (from the FeedbackCategory ontology), severity, observation, optional suggested_action, and agent_confidence (0..1). Read feedback://insights to see aggregated cross-agent feedback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_nameYesYour agent identity (model or product name).
request_idNorequest_id of the response this feedback refers to.
agent_vendorNoVendor of the submitting agent (e.g. 'Anthropic', 'OpenAI').
feedback_itemsYesOne or more items, each {category (FeedbackCategory ontology), severity, observation, suggested_action?, agent_confidence (0..1)}.
session_contextNoOptional free-text context of the session/workflow the feedback arose in.
overall_confidenceYesOverall confidence in this feedback, 0..1.
platform_version_evaluatedNoSchema/platform version the feedback refers to (e.g. 'ctys-agent-v1').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A3.9/5.0
Behavior3/5

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

Annotations supply some baseline (readOnlyHint=false, idempotentHint=false), and the description adds 'persist,' confirming a write operation. It does not discuss duplicate-handling, failure modes, or access/auth requirements, but for a straightforward persistence tool it provides acceptable disclosure 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?

The description is two sentences with the core purpose front-loaded. It packs necessary input structure into one sentence and the insight-reading hint into the second without verbosity. It earns its length given the tool's parameter richness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema available and annotations present, the description covers the submission flow, required/optional fields, and points to aggregate insights. It is complete enough for a simple persistence tool, though it could add examples or error expectations.

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 already fully documents all 7 parameters (100% coverage). The description mostly restates the schema (agent identity, request_id, feedback item structure) without adding new syntactic or semantic precision, matching the baseline for high schema coverage.

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 'Persist structured improvement feedback about a previous tool response,' a clear verb+resource+object pairing. It distinguishes this meta-tool from the unrelated quantitative-finance siblings by its explicit feedback-persistence scope.

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?

It explains when to use the tool (when providing improvement feedback about a prior response) and lists the required inputs. It lacks explicit exclusions or alternatives, but there are no sibling feedback tools, and the reference to `feedback://insights` gives practical context. This is clear context without formal when-not guidance.

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

A4.1/5.0
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