hackshop
Server Details
Plan and build a physical body for your AI agent: boards, parts list, assembly and pairing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 3 tools
Each tool targets a distinct stage: assess_hackability evaluates a device, get_build_plan returns a build plan for a chosen device, and plan_gadget plans a whole gadget from an idea. There is mild overlap between get_build_plan and plan_gadget since both can emit build guidance for devices, but the input contracts (device_id vs. free-form idea with needs/budget) keep them mostly separable.
All three names use a consistent snake_case verb_noun style (assess_hackability, get_build_plan, plan_gadget). The verb choice varies (assess/get/plan) but the pattern is readable and predictable, a minor deviation from a strict single-verb scheme.
Three tools is on the thin side for a domain that involves device discovery, per-device build planning, and end-to-end gadget design. Each earns its place, but the surface feels minimal and could reasonably support a few more operations.
Core workflows (assess a device, get its build plan, plan a gadget) are covered, and assess_hackability doubles as id/substring discovery. However, there is no explicit catalog listing/search tool, nor any save/export/share or cost-comparison operation, leaving some notable gaps.
Available Tools
3 toolsassess_hackabilityAssess hackabilityBInspect
Look up a device by id, exact name or substring and return hackability, brick risk, firmware links, community size, build page and agent platform support. Input: device_name 1-200 chars.
| Name | Required | Description | Default |
|---|---|---|---|
| device_name | Yes | Device name or id, 1-200 characters. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It usefully discloses the fuzzy matching semantics (exact name or substring), which is behavioral information beyond the schema, but it does not state read-only status, auth requirements, or how ambiguous/multiple matches are resolved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences, front-loaded with the action and result set. The trailing 'Input: device_name 1-200 chars' largely duplicates the schema and is the one mildly wasteful element.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the return-value enumeration is partly redundant, and no annotations exist to offload the safety profile. The description is adequate for a single-parameter lookup but leaves match-precedence and multi-result behavior unstated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds genuine meaning beyond the schema by clarifying that device_name accepts an id, an exact name, or a substring, which the schema's plain 'Device name or id' does not convey.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('look up') and resource (device) and enumerates what it returns (hackability, brick risk, firmware links, community size, build page, agent platform support). It is clearly distinguishable from get_build_plan and plan_gadget by intent, though it never names those siblings or contrasts itself with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies lookup usage by explaining the matching modes (id, exact name, substring), but gives no explicit when-to-use guidance, no prerequisites, and no routing against the sibling tools get_build_plan and plan_gadget. An agent must infer when this is the right call.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_build_planGet a build planBInspect
Return the complete deterministic build plan for a catalog device id: parts, shopping list with buy_options and store URLs, steps, machine-readable assembly, commands, links, caveats and an agent-ready brief. Input: device_id 1-200 chars.
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | Yes | Catalog device id, 1-200 characters. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden; it does disclose the useful trait that the plan is 'deterministic', which tells the agent repeated calls yield identical output. However, it says nothing about read-only safety, error behavior for unknown ids, latency, or whether links/URLs can go stale.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the verb and the deliverable, and the closing input line is compact. The long content enumeration is dense but informative rather than padded, so it largely earns its space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with an output schema, the description is nearly sufficient, and it helpfully previews the plan's sections. The remaining gap is the absence of any guidance on sibling selection and on failure modes for invalid device ids.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the sole device_id parameter is fully documented in the schema, and the description merely restates '1-200 chars'. It adds no meaning such as where to obtain a valid catalog device id or what happens when the id is not found.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Return') and resource ('complete deterministic build plan') and enumerates the payload contents (parts, shopping list, steps, commands, caveats, brief), so an agent knows exactly what it gets. It never references the sibling tools assess_hackability or plan_gadget, so differentiation from siblings is left to inference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this tool versus the siblings plan_gadget or assess_hackability, and no exclusions or prerequisites beyond the implicit requirement of a catalog device id. The agent must infer the routing decision entirely on its own.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
plan_gadgetPlan a Muse gadgetBInspect
Deterministically plan a physical body for an AI agent using Meta Muse boards. Inputs: idea 3-2000 chars; platform one of muse-esp32, muse-linux, any (default any); budget_usd positive number up to 100000; owned_device_ids up to 50 catalog ids; needs values: voice, screen, images, touch, camera, air-sensors, e-ink, battery, round, home-tunnel, big-screen, compute, linux; size one of pocket, desk, wall, hidden, any (default any); limit 1-5 (default 3). Returns fit, notes, warnings, intake questions, picks, terms and next steps.
| Name | Required | Description | Default |
|---|---|---|---|
| idea | Yes | Gadget idea or use case, 3-2000 characters. | |
| size | No | Preferred size or placement: pocket, desk, wall, hidden, any. Default any. | any |
| limit | No | Number of picks to return: 1-5, default 3. | |
| needs | No | Optional explicit needs. Allowed: voice, screen, images, touch, camera, air-sensors, e-ink, battery, round, home-tunnel, big-screen, compute, linux. | |
| platform | No | Platform filter: muse-esp32, muse-linux, or any. Default any. | any |
| budget_usd | No | Optional hardware budget in USD. Must be greater than 0, max 100000. | |
| owned_device_ids | No | Catalog device ids the user already owns. Max 50. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the word 'deterministically' and enumerates the return sections (fit, notes, warnings, intake questions, picks, terms, next steps), which hints at a non-destructive planning read. But it never states that nothing is written, whether it requires auth or a catalog, or that results are recommendations rather than executed purchases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence front-loads the purpose well, but the remainder is a semicolon-chained parameter dump that largely duplicates the input schema nearly verbatim. It is not padded with fluff, but two-thirds of the text does not earn its place next to a 100%-covered schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so the description needn't explain return values, and it does cover the purpose plus all inputs. The remaining gap is routing relative to siblings and any behavioral caveats for a 7-parameter planning tool, which is a moderate rather than severe omission.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so every parameter is already documented with type, enum, default and bounds. The description restates the identical facts (ranges, defaults, allowed enum values) without adding format hints, interaction rules, or examples. Baseline 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'plan a physical body for an AI agent using Meta Muse boards', with the distinguishing adverb 'deterministically'. Clear purpose, but it never contrasts itself with sibling 'get_build_plan', which sounds like an adjacent planning/build step, so the agent must guess at the boundary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description is essentially an input inventory with no when-to-use or when-not-to-use guidance. Given the sibling set (assess_hackability, get_build_plan), the agent gets no signal about whether this is the first step, a prerequisite for get_build_plan, or an alternative to it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
- First observed
assess_hackability - First observed
get_build_plan - First observed
plan_gadget
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