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Glama

open_target

Open a CLI, web, Android, or Docker target and record its declared purpose, jurisdiction, and Terms of Service snapshot to begin black-box observation.

Instructions

Open a target and record intake (declared purpose, jurisdiction, ToS snapshot). target: cli:docker: | cli:build: | cli:local | web: | android:: | desktop:docker:. strict: every release needs a person's approval at a terminal. target_options (web): reset_command, reset_check_url, contract_selectors {source, selectors}, api_templates, profile {asset_hosts, ...}; see the observer guide.

Input Schema

NameRequiredDescriptionDefault
strictNo
targetYes
accountNo
purposeYes
real_namesNo
terms_textNo
jurisdictionNo
target_optionsNo
owner_declarationNo
max_actions_per_secondNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that intake records purpose, jurisdiction, and ToS, and that strict mode requires human approval at a terminal, but it omits what side effects occur, whether state persists, and how failures are surfaced for a stateful open operation.

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

Conciseness4/5

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

The description is front-loaded with the main action in the first sentence, followed by target formats and then strict/option details. It is dense but each sentence carries operational information; minor ellipses in the target_options profile list reduce clarity slightly.

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

Completeness3/5

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

An output schema exists, so return values need not be explained. However, for a 10-parameter, annotation-free tool with 0% schema coverage, the description leaves several parameters and nested target_options details undefined, relying on an external observer guide.

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

Parameters2/5

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

Schema description coverage is 0% across 10 parameters, so the description must compensate and only partially does. It documents target formats, strict, and some target_options keys, but purpose, jurisdiction, terms_text, owner_declaration, account, real_names, and especially max_actions_per_second receive little or no explanation.

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 clear verb and resource: 'Open a target and record intake (declared purpose, jurisdiction, ToS snapshot).' The enumerated target forms (cli:docker, web:, android:, desktop:) make the operation concrete. It does not explicitly contrast with siblings like discover_ui or probe_cli, but the scope is distinct enough.

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

Usage Guidelines3/5

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

Usage is implied as the first step before other target-scoped tools, but the description never states when to use this versus alternatives such as discover_ui, probe_cli, or learn_flow. There are no explicit exclusions or prerequisites beyond the strict-mode note.

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