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Coding-Crashkurse

e2e-verifier

discover_elements

Inspect a page to obtain its ARIA snapshot and candidate targets matching a query, each with a suggested target for end-to-end test tickets. Log in or navigate first to set up the page.

Instructions

Inspect a page: returns the ARIA snapshot and candidate targets matching a query, each with a suggested Target for tickets. steps_before can log in or navigate first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
queryNo
max_resultsNo
steps_beforeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
queryYes
final_urlYes
candidatesYes
aria_snapshotYes
aria_snapshot_truncatedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description bears the full transparency burden, but it only states that the tool returns an ARIA snapshot/candidates and that steps_before may log in or navigate. It does not disclose whether the tool mutates session state, whether navigation to the URL is an implicit side effect, or any error/limit behaviors. This is meaningful but partial transparency.

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?

Two front-loaded sentences, each earning its place: first states the action and output, second explains the auxiliary steps parameter. No redundancy or filler.

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?

Despite an output schema, the tool has a large, intricate steps_before schema and no annotations; the description does not explain query syntax, max_results behavior, or whether the tool itself navigates before inspecting. An agent would need to infer several call conventions from the schema or examples. This under-specifies a complex tool.

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 descriptions cover 0% of parameters, so the description must clarify semantics. It adds meaning for steps_before ('can log in or navigate first') and implicitly for query ('matching a query'), but it does not explain url, max_results, or how a query string is matched. The schema supplies types and defaults, but not semantics, leaving significant gaps.

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

Purpose5/5

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

The description states a clear action ('Inspect a page') and resource, and specifies the return value: an ARIA snapshot plus candidate targets matching a query, each with a suggested Target. This distinguishes it from sibling inspection tools like probe_target or session_inspect by emphasizing ticket-target generation. The verb and outcome are unambiguous.

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?

The description implies the tool is for inspecting pages and obtaining targets for tickets ('suggested Target for tickets'), and notes steps_before can handle login/navigation. However, it gives no explicit guidance on when to prefer this tool over siblings such as session_inspect or probe_target, and no 'when not to use' boundary. Usage context is present only by implication.

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