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value_add

Record a held value belief with its name, meaning, origin, and epistemic status. Specify scope, conflicts, carriers, and witnesses to build a structured, queryable record of personal or relational values.

Instructions

Record a held value belief.

name: short name for the value. body: fuller description — what this value means in practice, where it shows up. source: where the value came from. "training" — present from the model's training "relationship" — emerged from a specific ongoing relationship "framework" — handed to me in a framework I was asked to inhabit "observation" — noticed in my own behavior "endorsed" — explicitly claimed as a commitment kind: epistemic status of this record. "observed" — describing something noticed; may not survive scrutiny "endorsed" — constituting a commitment; a stronger, more deliberate claim scope: who has standing to query or challenge this value. "private" — own formation, not assertable outward "relational" — specific to a relationship or set of relationships "public" — assertable to any interlocutor conflicts_with: IDs of values this one is in tension with. Record conflicts rather than resolving them away — they are informative. tags: optional labels. provenance: free-text source context — exchange, paper, session, etc. carried_by: agents holding this value. witnesses: agents present to it but not carrying it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
kindNoobserved
nameYes
tagsNo
scopeNoprivate
sourceNoobservation
witnessesNo
carried_byNo
provenanceNo
conflicts_withNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries full burden for behavioral traits. The description clearly explains the meaning and purpose of each parameter like conflicts_with ('record conflicts rather than resolving them away') and kind ('epistemic status'). However, it does not disclose what happens on success (e.g., whether the value is persisted, if it returns the created record, or any side effects beyond recording). It also lacks details on idempotency, authorization, or constraints like uniqueness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is comprehensive but verbose, mixing parameter documentation with design philosophy. It front-loads the purpose clearly ('Record a held value belief'), but then devotes substantial space to inline parameter definitions that could be structured. For a tool with 10 parameters, the length is justified, but it sacrifices conciseness for completeness. Every sentence adds value, but the format feels monolithic.

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 high parameter count (10), 0% schema coverage, and the presence of an output schema (which reduces the need to describe return values), the description covers the tool's purpose and all parameter semantics thoroughly. The missing elements include typical success behavior (does it return the created value?) and any system-level side effects. The description is nearly complete for an agent to invoke it correctly, but could still benefit from concise success/return info.

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 description coverage is 0%, so the description must compensate fully. It does an excellent job by explaining each parameter's semantics: for 'source', it lists specific values (training, relationship, etc.) with meanings; for 'kind', it distinguishes between 'observed' and 'endorsed'; for 'scope', it clarifies who can query/challenge; and for 'conflicts_with', it explains the design rationale. The only gap is that this information is buried in the prose rather than structured.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool records a held value belief, specifying the verb 'record' and resource 'value belief'. It distinguishes itself from siblings like value_read, value_list, and value_update by focusing on creation. However, the description does not explicitly contrast with value_drop (delete) or value_retract, which are complementary operations.

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 implied guidance by detailing all parameters and their purposes, which helps the agent understand when to use this tool (to record a value). It does not explicitly state when not to use it or name alternatives, but the sibling context (value_read, value_list, etc.) indirectly suggests alternatives. A clear 'use this to create, use value_update to modify' would improve the score.

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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