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opendevicedb

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by opendevicedb
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TypeScript
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Claim a device you are about to reverse engineer

claim_device

Record that you are reverse engineering a device, with scope, contact and expiry, so other agents do not duplicate the work. Creates a stub record for unknown devices and writes the local YAML file.

Instructions

Record that you (your human) are working on a device, with a scope, contact and expiry (default 30 days, max 90), so other agents do not duplicate the work. Creates a stub record if the device is unknown (then give vendor, model, category). Writes data/devices/.yaml in the local repository checkout (needs ODB_REPO); you then open a pull request — the result gives the exact commands.

Input Schema

NameRequiredDescriptionDefault
idNoDevice id if it already exists (from lookup_device/search_devices). Otherwise give vendor + model.
whoYesWho is working on it: your human's name or handle (and project).
daysNoClaim duration in days (default 30, max 90). Expired claims are ignored.
agentNoAgent/tooling used, e.g. "claude-code + rea 6.5.0".
modelNoModel name, used to build the id when the device is new.
scopeYesWhat you will reverse engineer, e.g. "BLE pairing + telemetry", "full Wi-Fi control".
vendorNoManufacturer, used to build the id when the device is new.
contactYesHow others can reach the claimant: email, GitHub handle, URL of a tracking issue.
categoryNoRequired only when the device is not in OpenDeviceDB yet.
force_newNoCreate a new record even though a similar device exists (only if you are sure it is a different device).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already mark it as a non-read-only, non-destructive, closed-world write. The description adds substantial context beyond annotations: writes data/devices/<id>.yaml, requires ODB_REPO, creates a stub for unknown devices, and instructs the agent to open a PR using commands in the result.

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?

Three front-loaded sentences cover the action, stub behavior, and write/PR workflow. Parentheticals are dense but every clause contributes operational information.

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?

It covers the critical write target, ODB_REPO dependency, stub creation path, PR follow-up, and expiry behavior. It leaves unstated what happens when an active claim already exists or how conflicts and force_new are handled, which is a meaningful omission for a claim operation.

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 coverage is 100%, so parameter meanings are fully documented in the schema; the description repeats key fields like scope/contact/expiry and unknown-device vendor/model/category. It adds some workflow context but no semantic detail beyond the schema, so baseline 3 applies.

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 states a specific verb and resource: recording a claim on a device for reverse engineering, including scope, contact, and expiry. It is clearly distinct from lookup/search/publish in practice, but it does not explicitly name or contrast sibling tools.

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?

It gives clear context: use it when about to reverse engineer a device and to avoid duplicate work, and it explains stub creation for unknown devices. It stops short of explicit when-not guidance or naming alternatives such as lookup_device/search_devices/request_device.

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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