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ADIKANT

datalens-dev-mcp

by ADIKANT

Read Project Live Summary

dl_read_project_live_summary

Read and normalize a project live workflow summary JSON for validating, dry-running, applying, or publishing DataLens dashboard changes.

Instructions

Read and normalize a project live workflow summary JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNoProject-live action.dry_run
publishNoRequest publish behavior.
project_rootYesLocal project root..
summary_pathNoSummary JSON path inside project.
workflow_nameNoManifest workflow name.
Behavior2/5

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

No annotations exist, so the description must fully disclose behavior. It indicates 'Read' (implying read-only) but does not elaborate on normalization specifics, side effects (if any), required permissions, or output characteristics. The description is minimal and leaves many behavioral questions unanswered.

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?

The description is a single sentence, which is concise but lacks structure. It does not front-load the most critical information or break into sections. While not verbose, it is too terse to convey necessary detail.

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?

Given the tool has 5 parameters, no output schema, and no annotations, the description is insufficient. It fails to explain what 'normalize' means, how the output is structured, or how it relates to sibling tools. The complexity of the tool demands a richer description.

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 the parameter descriptions are present. The tool description adds no additional meaning beyond the schema's own descriptions (e.g., 'Project-live action.'). Thus, the baseline of 3 applies; the description neither enhances nor detracts from parameter understanding.

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 clearly states the verb 'Read' and the resource 'project live workflow summary JSON', and introduces the concept of 'normalize'. However, it does not differentiate from sibling tools like dl_readback_and_report or dl_read_object, which also read data. The purpose is specific but not uniquely positioned.

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 is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions. The description is silent on usage scenarios, leaving the agent without decision support.

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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