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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Archive Saved Thesis

delete_thesis
DestructiveIdempotent

Soft-delete a saved thesis: status flips to archived (the row stays for audit / re-scoring). Idempotent — archiving an already-archived thesis succeeds. Hard-delete is not supported by design; future versions may expire archived theses after N years. This does not delete the claims linked to the thesis — use delete_claim for those. Tier: paid + free (sample rejected).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thesis_idYesId returned by `save_thesis` or `list_theses`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaYesProvenance envelope — data lineage for every MCP response
statusYes
thesis_idYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already indicate idempotent and destructive. The description adds valuable context: soft-delete semantics, audit trail retention, idempotency guarantee, and lack of hard-delete support. No contradictions.

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?

Four sentences, each adding value. Front-loaded with core action and key traits (soft-delete, idempotent). No fluff, concise and well-organized.

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 single parameter, presence of output schema, and rich annotations, the description covers all necessary behavioral details (audit, idempotency, claim linkage, tier) completely.

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?

Only one parameter with 100% schema coverage. Schema already describes thesis_id as returned by save_thesis/list_theses. Description doesn't add meaning beyond schema, so baseline 3.

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 clearly states that the tool soft-deletes a thesis by flipping status to 'archived'. It distinguishes from hard-delete and from deleting linked claims, which is precise and differentiates from sibling tools like delete_claim.

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?

Explicitly states when to use (soft-delete a thesis) and when not to (use delete_claim for claims). Also mentions tier restrictions ('paid + free (sample rejected)'), providing clear context for invocation.

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

A4/5.0
Disambiguation5/5

Each tool has a distinct purpose with detailed descriptions that clarify differences. Overlaps like get_peer_comparables vs screen_universe are well-differentiated by scope (single company vs cross-sectional). Similarly, get_insider_sentiment vs get_smart_money_flow are clearly distinguished by data sources and methodology.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., create_report, get_financial_ratios, delete_alert). No mixing of conventions or inconsistent verbs.

Tool Count2/5

With 69 tools, the count far exceeds the 25+ threshold for 'too many'. While the domain is broad, the sheer volume likely overwhelms agents and increases selection complexity.

Completeness4/5

The tool set covers a wide range of SEC filings, ratios, smart-money data, alerts, reports, and more. Minor gaps exist (e.g., no options or detailed debt data), but most analyst workflows are supported.

Resources