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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Save Investment Thesis

save_thesis
Idempotent

Persist a directional investment thesis (bull / bear / neutral) on a ticker. The thesis becomes part of the caller's private research diary; pair with list_theses + score_thesis_outcome to track conviction-vs-outcome over time. Pass idempotency_key for at-most-once semantics from a retrying agent.

Use this AFTER the agent has finished its analysis, not before — the thesis records the conclusion, not the question. Pair with source_report_id to link the thesis back to a published report so the buyer's thesis-tracking carries provenance.

Tier: all paid + free tiers (sample tier rejected — sample is guest access with no customerId binding). Flat 10,000-thesis anti-abuse cap per account (archiving frees a slot; never a tier limit).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewYesDirectional view: bull (expect outperformance), bear (under), neutral (mean-revert).
notesNoFree-form rationale, ≤4000 chars. Stored verbatim; trim before submitting.
tickerYesUS-listed ticker. Case-insensitive — normalised to upper. E.g. 'AAPL'.
convictionYes1 = low conviction (gut feel) → 5 = high conviction (deep analysis).
visibilityNoPhase 3: 'private' (default) is owner-only; 'unlisted' is visible at a known direct URL; 'public' surfaces on the author's /[handle] profile and contributes to their reputation score.private
horizon_daysYesInvestment horizon in days. 1 day–5 years (1825d). The grader uses this to pick the as-of period.
idempotency_keyNoOptional client-supplied key. If a previous `save_thesis` from the same user used this key, the existing thesis is returned instead of creating a duplicate.
source_report_idNoOptional id of a report (from `create_report` / `publish_report`) that contains the supporting analysis.
thesis_at_price_centsNoOptional snapshot of the ticker's market price (integer cents) at thesis creation. Used by future versions of the grader that mix in price returns; null for now is fine.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaYesProvenance envelope — data lineage for every MCP response
thesisYes
capacityYes
deduplicatedYes

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate idempotentHint=true and destructiveHint=false. The description adds valuable behavioral context: the thesis is stored in a private research diary, there is a 10,000-thesis anti-abuse cap per account, and the tool is for recording conclusions after analysis. No contradictions with annotations. The additional details enhance transparency beyond structured fields.

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 concise yet packed with essential information. It is front-loaded with the primary action and quickly moves to usage guidance, pairing suggestions, and tier/cap details. Every sentence adds value without redundancy, making it efficient for an agent to parse.

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?

Given the tool's complexity (9 parameters, 4 required, output schema exists), the description covers purpose, timing, idempotency, tier caps, and provenance linking. It does not detail return values or error cases, but these are likely covered by the output schema. The description is sufficiently complete for an agent to select and invoke the tool correctly in most contexts.

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?

Schema coverage is 100% with well-described parameters, giving a baseline of 3. The description adds meaning by explicitly referencing 'idempotency_key' for at-most-once semantics and 'source_report_id' for linking to reports, and it provides tier restrictions that affect usage. These additions go beyond the schema descriptions, justifying a slightly higher score.

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 the tool persists a directional investment thesis on a ticker, using a specific verb ('persist') and resource ('thesis'). It distinguishes from siblings by explicitly mentioning pairing with 'list_theses' and 'score_thesis_outcome', and the action is well-differentiated from other thesis-related tools like delete_thesis and publish_thesis.

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 provides explicit guidance on when to use the tool: 'Use this AFTER the agent has finished its analysis, not before'. It also advises on passing 'idempotency_key' for retries and pairing with 'source_report_id' for provenance. However, it does not explicitly state when to use alternatives like 'get_thesis' or 'delete_thesis', though the pairing context partially addresses this.

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.

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