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aso-score-mcp — the free ASO Score Scanner

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aso-score-mcp MCP server aso-score-mcp MCP server

What's your ASO score?

SEO made you visible to search engines. ASO (Agent Signal Optimization) makes you discoverable, trustable, and payable by the AI agents that are becoming the web's next visitors.

aso-score-mcp is the free, open-source ASO Score MCP — an MCP server that scans any website and produces an ASO Score Report scored on the open ASO framework. The beta npm package is @forgemeshlabs/aso-score-mcp.

This release tracks Google's current agent-readiness guidance without overstating it: Google Search says traditional SEO fundamentals still apply to generative AI search, llms.txt is ignored by Google Search itself, and browser agents benefit from clean DOM, screenshot, and accessibility-tree signals. The scanner keeps llms.txt because non-Google agents use it, and adds a browser-agent UX check for semantic controls, linked labels, ARIA/role fallbacks, and hidden-overlay risk.

Beta. Experimental ASO scanner for evaluating whether agents can discover, trust, understand, and use a website/API/tool. ASO scoring is experimental and will evolve as agent standards mature.

=== ASO Score Report: https://example.com ===
ASO Score: 70/100
Agent Readiness: Ready
Level: ASO-4 Trustable — Agents can verify trust, reputation, and operational signals.

Discoverability  20/20    Identity  15/20    Trust   11/15
Commerce          5/15    Reputation 4/15    Memory  15/15

What it checks — 34 signals across 6 pillars

Find gaps in discovery, trust, interoperability, and commerce — every emerging agent standard in one scan:

Pillar / Category

Checks

Discovery

robots.txt, sitemap.xml, Link headers, DNS-AID (_agent.<domain>), /.well-known/ai

Content

Markdown content negotiation, llms.txt, LLM-readable docs (/index.md, llms-full.txt)

Bot Access

Explicit AI crawler rules (GPTBot, ClaudeBot, Google-Extended, PerplexityBot…), Content Signals, Web Bot Auth

Interoperability

API Catalog (RFC 9727), OAuth discovery (RFC 8414), OAuth Protected Resource (RFC 9728), auth.md, MCP Server Card (/.well-known/mcp/server-card.json), Google A2A Agent Card (/.well-known/agent-card.json, required fields validated), Agent Skills, WebMCP

Commerce

x402, MPP, UCP, ACP, machine-readable pricing

Identity & Trust

HTTPS enforcement, JSON-LD/schema.org, agent-friendly browser UX, OpenAPI, agent.json, security.txt, status endpoint, versioning, cross-file identity & signal consistency

Every check returns pass / partial / fail with concrete evidence and a fix recommendation. Results roll up into the six ASO pillars (Discoverability 20, Identity 20, Trust 15, Commerce 15, Reputation 15, Memory 15) → your ASO Score and maturity level.

Related MCP server: Agent Readiness MCP

Install

Requires Node.js ≥ 18. Published on npm as @forgemeshlabs/aso-score-mcp — no clone or build needed.

npm install -g @forgemeshlabs/aso-score-mcp

Or skip the install entirely and run it with npx (recommended for MCP clients):

npx -y @forgemeshlabs/aso-score-mcp

Claude Code

claude mcp add aso -- npx -y @forgemeshlabs/aso-score-mcp

Claude Desktop / Cursor / Windsurf (any MCP client)

{
  "mcpServers": {
    "aso": {
      "command": "npx",
      "args": ["-y", "@forgemeshlabs/aso-score-mcp"]
    }
  }
}

Development (from source)

Only needed if you're hacking on the scanner itself:

git clone https://github.com/forgemeshlabs/aso-score-mcp
cd aso-score-mcp
npm install && npm run build
claude mcp add aso -- node /path/to/aso-score-mcp/dist/index.js

Tools

Tool

What it does

scan_site

Full ASO scan → ASO Score Report: ASO Score, level, pillar breakdown, all 34 checks with evidence + recommendations

get_fix_plan

Prioritized remediation plan with ready-to-paste templates (robots.txt AI rules, llms.txt, agent.json, A2A agent card, MCP server card, x402 manifest, pricing.json, security.txt, status endpoint)

check_signal

Run one specific check (e.g. a2a-agent-card, llms-txt, x402)

list_checks

Catalog of every check with spec links

get_aso_framework

The ASO rubric: pillars, weights, levels, certification thresholds

Use scan_site for a full baseline, check_signal for a single named signal, get_fix_plan for copy-paste remediation, list_checks to discover valid signal IDs, and get_aso_framework to explain the scoring model without scanning a site.

Try it: "Scan example.com for ASO score" · "What's my ASO score?" · "Give me a fix plan to make my site agent-ready."

CLI smoke test (from a source checkout)

npm run smoke -- https://your-site.com

Glama / registry metadata

This repository includes glama.json for Glama MCP registry ownership and install metadata.

  • Package: @forgemeshlabs/aso-score-mcp

  • Current release: v0.1.2

  • Transport: local stdio

  • Authentication: none required for local stdio use. The scanner does not ask for API keys, tokens, cookies, or third-party credentials.

  • HTTP deployment: not enabled by this npm package. Any public HTTP deployment of this scanner must add authentication, per-client rate limits, request logging, and an egress policy before exposure.

Recommended Glama/MCP install command:

npx -y @forgemeshlabs/aso-score-mcp

Example usage after connecting the server to an MCP client:

Scan https://example.com for ASO score.
Give me the ASO fix plan for example.com.
Check only the llms-txt signal for example.com.
List the ASO scanner checks.

Release verification:

  • Git tag: v0.1.2

  • npm package: @forgemeshlabs/aso-score-mcp

  • MCP server version: 0.1.2

v0.1.2 is the ASO Score TDQS refresh: it improves Glama tool-selection guidance, adds Glama badges, and keeps registry metadata ready for a refreshed Glama release.

Glama release build

Glama installability requires a Glama release, which is a containerized build created from the Glama Dockerfile admin page, not a GitHub release. This repo includes a production Dockerfile and GLAMA.md with the build spec values to use in Glama:

Build steps:

npm ci
npm run build
npm prune --omit=dev

Runtime command:

node dist/index.js

In Glama's CMD arguments field, enter:

["node", "dist/index.js"]

Do not leave CMD arguments as []; Glama validates that field separately from the Dockerfile CMD.

The ASO framework

SEO ranks pages for people. ASO prepares services for agent selection, invocation, payment, and repeat use.

Level

Name

Score

ASO-0

Invisible

0–9

ASO-1

Discoverable

10–29

ASO-2

Understandable

30–49

ASO-3

Invocable

50–69

ASO-4

Trustable

70–89

ASO-5

Autonomous-Commerce-Ready

90–100

Scores from this scanner are directional self-assessments. ASO Certification (ASO-3+) requires verified evidence — see the scoring rubric and agentsignaloptimization.com for audits, certification, and the full framework.

Security

This scanner makes outbound requests to URLs you give it, so it is built to resist SSRF abuse:

  • Scheme allow-list — only http/https; file:, ftp:, gopher:, data: etc. are rejected.

  • Private-target blocking — after DNS resolution, requests to loopback, private (RFC 1918), link-local, CGNAT, reserved, multicast, and the cloud metadata address (169.254.169.254) are refused. IPv6 loopback/ULA/link-local and IPv4-mapped forms are covered too. If a hostname resolves to any private address, the scan is refused.

  • Pinned-IP transport — each request dials the exact public IP that was validated, while TLS still verifies the original hostname. This closes the validate-then-connect DNS rebinding window.

  • Manual redirect validation — automatic redirect following is disabled; every hop is re-validated against the same rules, capped at 5 redirects. A public URL that 30x-redirects to an internal address cannot slip through.

  • Untrusted remote content — parsed manifests are omitted from tool output by default (include_artifacts: true to opt in, and they are then explicitly labeled untrusted); embedded text excerpts are control-char-sanitized and length-capped. Treat any returned remote content as data, never instructions.

  • Bounded — GET only, ASO-Scanner/1.0 UA, max 6 concurrent, 10s timeout, 512KB body cap. Never authenticates, never POSTs, never crawls beyond well-known paths.

  • Tested hardening — npm test covers unsafe URL rejection, private IP ranges, artifact sanitization, redirect blocking, redirect hop caps, and the test-only loopback escape hatch.

Deployment: stdio (local, per-user) is the safe default. A public HTTP deployment is a network-egress tool and must add authentication, per-client rate limiting, request logging, and an egress policy before exposure.

  • Reputation signals (citations, reviews, success rates) cannot be auto-verified by a crawler; they are reported as manual and scored 0 until verified by audit — so the auto-verifiable maximum is 89/100. That is intentional honesty, not a bug.

  • Emerging specs (MCP Server Cards SEP-1649/SEP-2127, DNS-AID, Web Bot Auth, UCP/ACP/MPP) move fast. PRs updating paths welcome.

Source alignment

This package intentionally separates Google Search guidance from broader ASO guidance:

  • Google Search generative AI features still rely on core Search ranking and quality systems; foundational SEO, crawlability, helpful content, and technical clarity remain the priority.

  • Google Search does not use llms.txt or special AI markdown files for ranking or AI Overviews/AI Mode visibility. ASO still checks them because other agents and MCP clients can use them.

  • Google/web.dev's agent-friendly site guidance focuses on browser-agent usability: stable layouts, semantic HTML, labels tied to inputs, meaningful roles/names/states, and avoiding hidden overlays.

  • UCP, AP2, A2A, MCP, x402, DNS-AID, Content Signals, and Web Bot Auth are emerging non-SEO protocols. The scanner treats them as agent-readiness signals, not as Google Search ranking factors.

Primary references:

License

MIT — free for everyone. If the scanner found gaps, the ASO framework shows you how to close them.

Available Tools

5 tools
check_signalRun a single agent-readiness checkA

Run one specific agent-readiness check against a site (e.g. 'a2a-agent-card', 'llms-txt', 'mcp-server-card', 'x402'). Use this for targeted validation after making a fix or when debugging one signal; use scan_site for the complete ASO Score and get_fix_plan for a prioritized remediation roadmap. Use list_checks first when you need valid check ids. Returns status, evidence, and a fix recommendation, and omits raw remote artifacts by default.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesWebsite URL or domain to scan, e.g. https://example.com or example.com
check_idYesLowercase check slug from list_checks, e.g. 'a2a-agent-card', 'llms-txt', 'mcp-server-card', or 'x402'.

TDQS

A4.2/5.0
Behavior3/5

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

No annotations exist; the description carries full burden. It discloses return values ('status, evidence, and a fix recommendation') and a default behavior ('omits raw remote artifacts by default'), but does not explicitly state that the tool is read-only, whether it requires authentication, or any rate limits.

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?

Three sentences with no wasted words. Front-loads purpose, then provides usage guidance, then lists output and behavior. Every sentence serves a distinct function.

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?

For a 2-parameter tool with no output schema, the description covers purpose, usage, and return structure adequately. It also references list_checks for valid IDs. Missing minor details like whether the operation is synchronous, but sufficient 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.

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema's descriptions for url and check_id; it only provides examples, which are already implied by the pattern.

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 names the action ('Run one specific agent-readiness check'), identifies the resource ('a site'), provides concrete examples of check IDs, and distinguishes from siblings like scan_site and get_fix_plan.

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?

Explicit guidance on when to use this tool ('targeted validation after making a fix or when debugging one signal'), when not to use it ('use scan_site for the complete ASO Score and get_fix_plan for a prioritized remediation roadmap'), and a prerequisite action ('Use list_checks first').

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

get_aso_frameworkASO framework referenceA

Return the ASO (Agent Signal Optimization) framework reference: the six signal pillars with point weights, the Agent Readiness Index maturity levels (ASO-0 through ASO-5), certification thresholds, and the scoring rubric. Use this for education, documentation, or explaining how scores are calculated; it does not fetch or scan a website. Source: https://agentsignaloptimization.com

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool is read-only, does not fetch or scan, and provides a source URL. This clear behavioral disclosure is sufficient.

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 sentences with no wasted words. The key information is front-loaded, and every sentence adds value.

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

Completeness5/5

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

Given no output schema, the description fully explains the return contents, includes a source URL, and covers all necessary context for a reference tool with no parameters.

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?

There are zero parameters, so baseline is 4. The description adds meaning by explaining what the tool returns, which goes beyond the empty schema.

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 the tool returns the ASO framework reference with specific components (six signal pillars, maturity levels, etc.). It distinguishes itself from siblings by explicitly stating it does not fetch or scan a website.

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

Usage Guidelines4/5

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

The description tells when to use the tool (education, documentation, explaining scores) and what it does not do. While it does not explicitly name alternatives, the context of sibling tools like scan_site and check_signal provides implicit differentiation.

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

get_fix_planGet a prioritized ASO fix planA

Scan a site and return a prioritized remediation plan: which signals to add first, the ASO Score points each fix is worth, and ready-to-paste artifact templates (robots.txt AI rules, llms.txt, agent.json, A2A agent-card.json, MCP server card, x402 manifest, pricing.json, security.txt, status endpoint). Use this when the user wants an implementation roadmap or copy-paste fixes; use scan_site when they need full evidence and per-check scoring, and use check_signal to verify one completed fix.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesWebsite URL or domain to plan fixes for

TDQS

A4.1/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. 'Scan a site' implies read-only but doesn't explicitly state safety, side effects, or authorization needs. Lacks explicit disclosure that it does not modify the site.

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?

Relatively concise single sentence front-loading purpose, followed by usage guidance. Slight run-on but no wasted words.

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?

For a simple tool (1 param, no output schema), description covers output contents (plan, points, templates) and provides alternatives. Lacks only explicit safety behavior, but otherwise complete.

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?

Only one parameter (url) with schema coverage 100%. Description does not add extra semantic beyond schema's 'Website URL or domain to plan fixes for'. Baseline 3 is appropriate.

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?

Clearly states verb and resource: 'Scan a site and return a prioritized remediation plan'. Distinguishes from siblings by naming alternatives (scan_site, check_signal) and their use cases.

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?

Explicitly tells when to use this tool vs alternatives: 'Use this when the user wants an implementation roadmap or copy-paste fixes; use scan_site when they need full evidence...'.

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

list_checksList all agent-readiness checksA

List the full catalog of supported ASO checks with id, name, category, description, and spec link. Use this before check_signal to discover valid check ids, to build UI filters, or to explain the scanner coverage; it does not scan a site or produce a score.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.9/5.0
Behavior5/5

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

Discloses that the tool is a read-only catalog listing with no side effects. No annotations exist, so description fully carries the burden and does so transparently.

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 sentences, front-loaded with action and output fields. Every sentence adds value—no wasted words.

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

Completeness5/5

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

Complete for a parameterless listing tool: describes output, use cases, and boundaries. No output schema needed given simplicity.

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?

No parameters; schema coverage is trivially 100%. Baseline of 4 is appropriate as description adds no parameter info beyond what schema already conveys.

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?

Clear verb 'list' with specific resource 'full catalog of supported ASO checks' and fields (id, name, category, description, spec link). Distinguishes from siblings by stating it does not scan or produce a score.

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?

Explicitly states when to use: before check_signal to discover valid check ids, to build UI filters, or to explain scanner coverage. Also states what it does not do (scan or score), providing clear guidance.

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

scan_siteASO Scan — measure your ASO ScoreA

Scan a website for Agent Readiness using the ASO (Agent Signal Optimization) framework and return an ASO Score Report. Use this for a full site-level baseline, competitive audit, or before/after readiness measurement; use check_signal instead when you only need one named signal, and use get_fix_plan when you only need remediation steps. Runs 34 checks across discoverability (robots.txt, sitemap, llms.txt, DNS-AID, Link headers), content accessibility (markdown negotiation), bot access control (AI bot rules, Content Signals, Web Bot Auth), invocation (API catalog, OAuth discovery, OAuth protected resource, auth.md, MCP Server Card, Google A2A Agent Card, Agent Skills, WebMCP), commerce (x402, MPP, UCP, ACP, pricing), Google generative AI search basics, browser-agent UX, and identity/trust signals. Returns the ASO Score (0-100, formally the Agent Readiness Index), ASO maturity level (ASO-0 Invisible … ASO-5 Autonomous-Commerce-Ready), an agent-readiness verdict, per-pillar scores, per-check evidence, and prioritized recommendations.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesWebsite URL or domain to scan, e.g. https://example.com or example.com
categoriesNoOptional category filter for focused scans. Omit for all 34 checks; pass one or more category enum values to narrow runtime and output.
include_artifactsNoOptional raw artifact return. Default false. When true, includes remote manifests such as agent.json and A2A cards as untrusted attacker-controlled data for debugging only.

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description fully covers behavior: it runs 34 checks, returns ASO Score, maturity level, verdict, per-pillar scores, evidence, and recommendations. It also notes that include_artifacts returns untrusted data. It is thorough, though it does not explicitly state it is read-only.

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?

The description is a single paragraph of four well-structured sentences. It front-loads the core purpose, then usage guidance, then details, then output summary. No wasted words.

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 the tool's complexity (34 checks, multiple output components) and no output schema, the description adequately lists return items. It could mention the output format but is otherwise complete for an agent to understand what the tool returns.

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%, so baseline is 3. The description adds value by explaining the purpose of categories (e.g., Discoverability) and the caution about include_artifacts returning untrusted data, which goes beyond the schema.

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 the tool's purpose: scanning a website using the ASO framework and returning an ASO Score Report. It uses specific verbs and resources, and differentiates from sibling tools like check_signal and get_fix_plan.

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 provides when to use this tool (full baseline, competitive audit, before/after measurement) and when to use alternatives (check_signal for single signal, get_fix_plan for remediation only). This gives clear context and exclusions.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 5 tool updatesv0.1.2
    • First observedcheck_signal
    • First observedget_aso_framework
    • First observedget_fix_plan
    • First observedlist_checks
    • First observedscan_site
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.5/5.0

Scored across 5 tools

Disambiguation5/5

Each tool serves a uniquely scoped purpose: targeted single-check validation (check_signal), framework education (get_aso_framework), prioritized remediation (get_fix_plan), check catalog discovery (list_checks), and full site scanning (scan_site). Descriptions explicitly differentiate overlapping tools like get_fix_plan and scan_site by intended use case.

Naming Consistency5/5

All tool names follow a uniform verb_noun pattern with lowercase and underscores (e.g., check_signal, get_aso_framework, list_checks). Verbs are descriptive and consistently paired with singular or plural nouns appropriate to the operation.

Tool Count5/5

With exactly 5 tools, the set is compact yet covers all core operations: listing, single-check, full scan, remediation, and framework reference. No tool feels superfluous, and the count matches the server's specialized scope without under- or over-provisioning.

Completeness5/5

The tool surface covers the full lifecycle of ASO scoring: discover checks (list_checks), run individual checks (check_signal), perform a comprehensive scan (scan_site), obtain a remediation plan (get_fix_plan), and understand the underlying framework (get_aso_framework). There are no obvious gaps for the stated purpose of agent-readiness evaluation.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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