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lts_project

Get the complete LTS picture for a single project: all LTS records with computed fields (is_expired, days_until_expiry), summary counts, and the primary LTS number. Pass either a project UUID or a project name (fuzzy matched).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdNoProject UUID. Takes priority over projectName if both provided
projectNameNoProject name or slug for fuzzy lookup. Matched as a literal substring; use * as a wildcard. A term of only wildcards matches nothing. Use when you don't have the UUID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / projectName / description
      Previous value: -"Project name or slug for fuzzy lookup. Use when you don't have the UUID"New value: +"Project name or slug for fuzzy lookup. Matched as a literal substring; use * as a wildcard. A term of only wildcards matches nothing. Use when you don't have the UUID"
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses what the call returns (records, computed fields, summary counts, primary number), but does not disclose edge-case behavior for fuzzy matching — such as what happens when a name matches multiple projects or nothing at all. These are material behaviors for an agent relying solely on this text.

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?

Two sentences, with the core purpose and return contents front-loaded in the first sentence. The second sentence is somewhat redundant with the schema's parameter documentation, so it does not strictly earn its place, which prevents a 5, but overall the description is tight and well-ordered.

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?

With no output schema and no annotations, the description must convey the return shape, and it does name the key outputs. However, it omits no-match/ambiguous-match behavior and does not describe the structure or size of the returned record set, leaving an agent guessing about edge-case outcomes.

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 the baseline is 3: both parameters are already fully documented, including the projectId priority rule, substring matching, wildcard semantics, and the no-wildcard-only rule. The description's 'Pass either a project UUID or a project name (fuzzy matched)' adds no meaning beyond the schema, merely summarizing it.

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 uses a specific verb ('Get') and precise resource ('the complete LTS picture for a single project'), and enumerates the return contents: LTS records with computed fields (is_expired, days_until_expiry), summary counts, and the primary LTS number. This clearly distinguishes it from the dimension-scoped siblings (lts_by_city, lts_by_developer, lts_by_law, lts_by_region) and from lts_records/lts_search, which are not the complete single-project picture.

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 'for a single project' phrasing provides clear context for the intended scenario, and the schema adds a 'Use when you don't have the UUID' hint for projectName. However, with 11 siblings, the description never explicitly states when to choose this over lts_check, lts_records, lts_search, or lts_stats, nor does it state when not to use it.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct aspect of LTS data (by city, developer, law, region, etc.) with no overlapping purposes. The descriptions clearly delineate their unique use cases.

Naming Consistency5/5

All tools follow the consistent pattern 'lts_<descriptive_noun_or_phrase>' using snake_case. The naming is uniform and predictable, aiding agent selection.

Tool Count5/5

With 12 tools, the set is well-scoped for a data query and analysis server. Each tool serves a clear function without redundancy or overload.

Completeness5/5

The tool set covers all necessary query dimensions (city, developer, law, region, expiry, stats, trends) and includes a search, check, and project-level view. No obvious gaps for a read-only analytics server.

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