Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Save Agent

save_agent

Create or update a standing agent — a saved {goal + tickers + schedule} that fires either a fixed step recipe (agent_type="workflow", free/deterministic) or an AI-directed team (agent_type="autonomous", charged — settles against the owner's BYO key first, falling back to the managed wallet only if funded). Upsert semantics: omit agent_id to CREATE a new agent; pass an existing agent_id to UPDATE it. There is no separate update_agent — this does both, matching save_watchlist/save_thesis's house style. agent_type is STRUCTURAL and immutable: always required, and on an update it is verified against the existing agent before anything is changed — passing a different agent_type than the agent already has is rejected (delete and recreate to change the type). steps (an array of {kind:"tool"|"sop", name, args, label?}) is required and non-empty when CREATING an agent_type="workflow" agent, and must be omitted for agent_type="autonomous" (use managed_model there instead, itself optional and only valid for agent_type="autonomous"). when picks the trigger: "manual" (fires only via run_agent or the Workspace UI) or "schedule" (requires a schedule object — cadence "weekly" needs day_of_week, "monthly" needs day_of_month). This tool does NOT itself fire a run — use run_agent for that. Tier: sp500+ (sample rejected).

Input Schema

TableJSON Schema

Name	Required	Description
`goal`	Yes	What this agent is trying to accomplish — drives an autonomous agent's AI-directed team, and documents intent for a workflow agent's fixed steps.
`name`	Yes	Human-readable label.
`when`	Yes	Trigger mode. "manual" fires only via run_agent/the UI; "schedule" requires the `schedule` object.
`steps`	No	Fixed step recipe for agent_type="workflow". Required + non-empty when CREATING a workflow agent; must be omitted for agent_type="autonomous".
`tickers`	Yes	US tickers this agent operates over. Normalised to uppercase.
`agent_id`	No	Omit to create a new agent; pass an existing agent's id (from save_agent/list_agents/get_agent) to update it.
`schedule`	No	Required when when="schedule"; ignored otherwise.
`agent_type`	Yes	STRUCTURAL and immutable. "workflow" = fixed step recipe, free/deterministic, requires `steps`. "autonomous" = AI-directed team, charged, may set `managed_model`.
`managed_model`	No	Managed-lane model override for agent_type="autonomous" only (e.g. when no BYO key is connected). Omit to use the account default.

Output Schema

TableJSON Schema

Name	Required	Description
`_meta`	Yes	Provenance envelope — data lineage for every MCP response
`agent`	Yes
`created`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 18, 2026

changedOutput schema / properties / _meta / properties / fundamentals_as_of / description

Previous value: -"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to."New value: +"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt in bulk. Use THIS — not `last_updated` — when telling a user how current the cross-sectional fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to. It is a floor for a single filer, not a ceiling: a filer with a live partition receives its filing, facts and ratios intraday (minutes after EDGAR dissemination), so an entity-scoped read may carry a filing newer than this; cross-sectional ranks (factor scores, earnings signals) refresh with the weekly bulk export."

AddedAug 4, 2026

TDQS

A5/5.0

Behavior5/5

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

Annotations only provide generic false hints, so the description carries the behavioral burden and meets it fully. It discloses upsert semantics, agent_type immutability with rejection on mismatch, charging behavior and BYO-key fallback, the fact that this tool does not fire runs, and the delete-and-recreate path for changing type. No contradiction with 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 long but every sentence earns its place by carrying a constraint or routing decision. It front-loads the core purpose and upsert semantics before diving into conditional rules, and the density is justified by 9 parameters and nested conditional logic.

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 complexity, the description covers all operational decisions: create vs update, workflow vs autonomous, manual vs schedule, charging implications, tier restriction, and the fact that execution happens elsewhere. With an output schema present, nothing critical an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds substantial cross-parameter meaning beyond the schema: agent_type is structural and immutable, steps is required for creating workflow agents and must be omitted for autonomous agents, managed_model is only valid for autonomous, and 'when' determines whether schedule is required. It also clarifies the create/update meaning of agent_id.

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 states a specific verb-resource pair ('Create or update a standing agent'), defines the object precisely as a saved {goal + tickers + schedule}, and clearly distinguishes itself from siblings such as run_agent, delete_agent, and list_agents. The detail about workflow vs autonomous variants leaves no ambiguity about what the tool is for.

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 explicitly tells the agent there is no separate update_agent, names run_agent as the tool to fire a run, and references the save_watchlist/save_thesis house style for upsert semantics. It also states the tier gate ('sp500+') and gives conditional guidance for when to use each agent_type and trigger mode.

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

All Valuein — SEC EDGAR Fundamentals & Smart-Money Data tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.