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by co.heista

Fleet — SEO Indexing-Recovery Scorecard

fleet_seo_recovery
Read-onlyIdempotent

One-row verification scorecard for the indexing-recovery plan (internal-linking-spec-v2): site-wide + /decode-specific orphan counts (200 but zero internal inlinks) from the latest crawl, Googlebot vs other-bot crawl activity over a window (default 7 days, max 180), and Google Search Console impressions/clicks/avg-position over the trailing 28 days — each figure compared against the pre-fix baseline (1,521 orphans, 7 Googlebot pages/wk, 2 GSC impressions). Use this to confirm PR-A/B/C landed and is moving the needle, not just that the code shipped. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoCrawler-hit window in days (default 7, max 180 — retention limit). GSC + orphan figures are always current-snapshot / trailing-28d.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description's 'Read-only' is redundant but consistent. It adds value by specifying default window (7 days), max window (180), and that GSC/orphan figures are trailing-28d snapshots, which aids agent understanding of data freshness.

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 efficient but dense, front-loading the purpose and key metrics. Every sentence adds value, though it could be slightly shorter without losing meaning. The structure is logical: purpose, data types, usage guidance.

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

Completeness4/5

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

Given no output schema, the description adequately outlines the return values (orphan counts, crawl activity, GSC metrics) and baseline comparisons. It covers behavior, window constraints, and intended use, making it sufficiently complete for an agent to invoke correctly.

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

Parameters4/5

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

Schema coverage is 100% for the single parameter 'days', with a description. The tool description adds context beyond the schema by explaining the default (7), max (180), and that GSC/orphan figures are unaffected by this parameter. This helps the agent set appropriate values.

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 clearly states it's a 'one-row verification scorecard' for the 'indexing-recovery plan', enumerating specific metrics (orphan counts, crawl activity, GSC data). It distinguishes itself from generic analytics or GSC tools by focusing on recovery verification with baseline comparisons.

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

Usage Guidelines5/5

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

The description explicitly advises when to use this tool: 'Use this to confirm PR-A/B/C landed and is moving the needle, not just that the code shipped.' This gives clear usage context and implies it's the right tool for this verification, differentiating it from other monitoring tools.

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

A3.7/5.0
Disambiguation4/5

Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.

Naming Consistency3/5

Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.

Tool Count2/5

112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.

Completeness4/5

The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.

Resources