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Dropspace

by io.github.JCLVSH
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update_persona

update a persona's name or writing samples

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "update_persona"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYespersona ID
nameNonew persona name
brand_kitNohow autopilot image slides look when autopilot posts as this persona; null clears it
custom_samplesNocustom writing samples (max 50)
reddit_samplesNoreddit writing samples (max 50)
tiktok_samplesNotiktok writing samples (max 50)
twitter_samplesNotwitter writing samples (max 50)
facebook_samplesNofacebook writing samples (max 50)
linkedin_samplesNolinkedin writing samples (max 50)
instagram_samplesNoinstagram writing samples (max 50)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations declare readOnlyHint=false and destructiveHint=false, so the agent knows this is a non-destructive mutation. The description adds nothing about merge-vs-replace semantics: it does not say whether omitted fields are preserved, whether sample arrays are replaced wholesale, or that brand_kit accepts null to clear it (that detail lives only in the schema).

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?

It is a single short clause with zero padding, which is good, but the brevity comes at the cost of coverage rather than precision. The most important scoping fact, that this edits an existing persona in place, is left implicit.

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

Completeness2/5

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

For a 10-parameter mutation tool with no output schema, the description is far too thin. It omits brand_kit, does not explain replacement semantics for the seven sample arrays or their 50-item caps, and says nothing about what a successful update returns.

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?

Schema description coverage is 100%, so every parameter is documented in the schema, including the per-platform sample arrays and the brand_kit sub-fields, which establishes a baseline of 3. The description adds no meaning beyond the schema and in fact narrows it, mentioning only name and samples while ignoring brand_kit.

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?

"update a persona's name or writing samples" gives a clear verb and resource, and 'update' distinguishes it from get_persona/create_persona/delete_persona. However it understates scope by omitting brand_kit, which is one of the schema's most substantial fields, so an agent may wrongly believe appearance settings cannot be changed here.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this instead of create_persona or finalize_persona, and no note on prerequisites such as needing an existing persona id. There is no mention of partial-update expectations or what happens when fields are omitted.

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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