Agent skill

SEO Answer Visibility

by markfulton in markfulton/ai-employees

Observe answer visibility for approved buyer questions, audit discoverability and file evidence-backed improvement cards.

MITAuto-check passed

Install SEO Answer Visibility

skills CLI
$ npx skills add markfulton/ai-employees --skill seo-answer-visibility -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install markfulton/ai-employees seo-answer-visibility --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/markfulton/ai-employees.git skills-src && mkdir -p .claude/skills && cp -r skills-src/employees/seo-employee/routines/seo-answer-visibility .claude/skills/seo-answer-visibility && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-answer-visibility
GitHub stars
495
Token cost
~2.1k tokens
SKILL.md length
1,160 words
Files
1
Skills in repo
60
Repo updated
First seen
Licence
MIT

At a glance

Observe answer visibility for approved buyer questions, audit discoverability and file evidence-backed improvement cards.

  • Works in 5 steps: Begin a recoverable run → Check eligibility and factual consistency → Sample actual answers → …
  • SKILL.md covers Shared work cycle, 0. Begin a recoverable run, 1. Check eligibility and… and 2. Sample actual answers, plus 4 more sections
  • Calls node

What it does

SEO Answer Visibility is an agent skill from markfulton/ai-employees. Observe answer visibility for approved buyer questions, audit discoverability and file evidence-backed improvement cards.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Open source AI Employees. 8 scheduled business roles, 60 routines, on Claude Code and 10 other harnesses. They drive your browser the way you do and improve every run. You own… The licence is MIT.

Example prompts

  • “/seo-answer-visibility”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Begin a recoverable run
  2. Check eligibility and factual consistency
  3. Sample actual answers
  4. Turn gaps into useful work
  5. Write the report and close

What it can do on your machine

Read from SKILL.md and the folder at commit 37bfe17. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Answer Visibility loads about 2.1k tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 1,160 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~36
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from markfulton/ai-employees at commit 37bfe17, republished under its MIT licence (© markfulton). 1,160 words, ~2,078 tokens.

Download SKILL.mdSave it as .claude/skills/seo-answer-visibility/SKILL.md (or your agent's skills folder).
name
seo-answer-visibility
description
Observe answer visibility for approved buyer questions, audit discoverability and file evidence-backed improvement cards.
metadata.internal
true

Shared work cycle

After the guard returns run, read WORK-CYCLE.md and your entry in work-profile.json. Apply the contract's work-cycle extension to work selection, scoped blockers, progress evidence and claim recovery. Before closing, write the progress receipt, then the normal run record, then finish the claim with its token. Preserve the remaining budget on a resume. A same-period run with a claim overrides only the legacy Step 0.2 exit/reset. All pause, release and browser guards still apply.

Answer visibility

Run node scripts/guard.mjs seo-answer-visibility --json first. A non-run verdict has already been recorded; exit without reading the rest of the kit. For a run verdict read CONTRACT.md, ROLE.md, CAPABILITIES.md, AEO-PLAYBOOK.md and your SCHEDULE.md row in full. This routine inherits every contract guard, status, state schema, mutex rule and output writer boundary. Never infer a time, budget or cadence from this document.

0. Begin a recoverable run

Read your row and compute its period key using the contract rules and local clock. Read state/seo-answer-visibility.json. Apply the contract's once-per-period check and atomic state update, recording last_period, started, the run id and progress before external work. A real guard run returns an atomic claim. Preserve its token and apply WORK-CYCLE.md recovery rules; an inspection with --no-record reserves nothing. Use the established mutex/stale-lock rules before browser work, and release only the lock you own on every exit. Do not modify another routine's state, schedule or active lock.

Resolve capabilities live. Prefer a confirmed connected read route, then an approved browser session, then a dated member-supplied observation. CAPABILITIES.md is the only vendor-to-capability map. No connector purchase, install, account creation, authentication or credential entry. An unavailable route is an explicit gap, not zero visibility. Read-only observation includes submitting the approved public buyer question to an existing authorized search/chat surface; never include private client notes, secrets or unpublished strategy in that question. Do not use a route whose use requires accepting terms or an unapproved paid action.

Read strategy/properties.md, strategy/answer-map.md, strategy/topic-map.md, the published ledger, the previous answer report, current observations and board/board.json. If properties are missing, record failed with intake as the blocker. If the answer map is missing, file one deduplicated research card for intake; continue an owned-page eligibility review, but never invent the client's target audience or question set.

1. Check eligibility and factual consistency

Pick the highest-priority owned target pages from the answer map within the remaining budget. Read their HTTP status, canonical, visible answer text, internal entry links and available robots/directive evidence. Record the exact URL, date, method and finding. Compare organization and service facts to the approved evidence in the map. A missing capability is unknown, not a failed SEO check. Stage one specific correction per observed problem; never alter robots, CDN, schema, a public profile or a live page from this routine.

2. Sample actual answers

Work the fixed question set in stable id order, resuming coverage without exceeding the row budget. Follow the AEO-PLAYBOOK observation contract exactly. Distinguish each consumer surface from any API route. Capture the answer and its cited links, not just a search snippet about an answer. If a mode does not use retrieval, label it and keep it out of grounded-search comparisons.

Write each observation as a validated UTF-8 JSONL line once, with a stable id of run id + question id + surface. On retries, check that id before appending. Save only the evidence needed to verify the claim, strip secrets and unrelated account information, and reference its local path. Never overwrite earlier observations. Login walls stop work on that surface immediately; record blocked-login using the contract and continue file work if possible. No captcha retries, session sharing or attempts to evade platform limits.

Show full SKILL.md (555 more words)Show less

3. Turn gaps into useful work

Review what cited pages actually answer, using permitted fetches. Do not copy competitor prose. Identify which important buyer question is unanswered, which assertion lacks proof, which business fact conflicts, or which owned page is technically unavailable. A competitor mention alone does not demonstrate a defect in the client's page.

Apply the playbook's action order. Append prioritized, deduplicated cards using CONTRACT.md's exact inbox schema and existing types; read that schema before writing. Use refresh for an existing page improvement, new-post only for a missing canonical answer, research for missing evidence, and technical or verify for an owner action. Set done_kind to member-action for owner actions and local-artifact for a kit-owned draft/publish deliverable. Set owner to seo-draft-run only for executable content work; do not route infrastructure or outreach into the drafting runner. Include the source question id, evidence path/date, target URL, expected deliverable, responsible party and acceptance check in the card's allowed text fields. Do not invent new JSON fields or card types. Only standup assigns card ids and changes board order. Persist normalized proposed_keys in this routine's state and check them before each append; only standup reads the inbox.

Acceptance examples: approved service facts agree on the cited pages; a buyer question has a direct sourced answer on the canonical page; a permitted case study includes its method and date; a target page passes the owner's indexability check. Never use "ChatGPT must recommend us" or an unsupported traffic target as acceptance.

4. Write the report and close

Write a dated report under tracking/answers/ and atomically replace tracking/answer-latest.md only after that report is complete. Include:

  • Scope: question-set version, date, surface, locale, mode and coverage.
  • Observations: mention/citation counts and denominators per surface, feature-trigger rate where relevant, unavailable counts and evidence links. Nulls never become false or zero.
  • Representation errors with the exact evidence and approved correction.
  • Work completed or proposed, with card ids and acceptance checks.
  • Next required owner action and the specific missing capability, if any.
  • Comparability limits and a clear distinction between search metrics, answer samples, referrals and conversions.

At budget, stop at the current question boundary, persist coverage and write a partial report. Do not resubmit a completed question to use up time. On failure retain the previous successful rolling report with its original date; write the new failure to your state and run record. If file work succeeded but external observation was unavailable, report partial and coverage unknown, with the precise blockers. Apply the closed statuses from CONTRACT.md rather than inventing an AEO status.

Finish with the standard run record through scripts/runlog.mjs and its documented input contract. Include output paths, card ids, progress, blockers and assumptions. Release your browser lock and close only your own tabs in a finally-style cleanup. A log failure uses the contract's UNRECORDED RUN fallback; never silently report success. This routine never publishes, contacts prospects, changes infrastructure, spends, or writes RELEASES.md.

Native Generative AI integration

Read GSC-GENERATIVE-AI.md for report definitions, ownership and validation. Before question sampling, collect native Generative AI impressions using the current property map. Append validated observations and write the dated native report. This work does not require an answer-question map or previously published kit content. If that map is absent, still read the mapped property report and continue factual eligibility checks.

Corrections

No corrections recorded yet. Preserve member corrections when upgrading.

© markfulton, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in employees/seo-employee/routines/seo-answer-visibility of markfulton/ai-employees.

Open the folder on GitHubat commit 37bfe17

Compare with similar skills

SEO Answer Visibility next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

SEO Answer Visibility compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
SEO Answer Visibility this skillmarkfulton/ai-employees495—~2.1kAutomated safety check: PassMIT
Langsmith ObservabilityOrchestra-Research/AI-Research-SKILLs13k3 repos~2.4kAutomated safety check: PassMIT
ObservabilityBuilderIO/agent-native7.1k—~7kAutomated safety check: PassNone
Observability And Instrumentationsickn33/agentic-awesome-skills47k1 repos~2.9kAutomated safety check: PassMIT
Agent Observabilitysickn33/agentic-awesome-skills47k2 repos~3kAutomated safety check: PassMIT
Frontend Observabilitysickn33/agentic-awesome-skills47k1 repos~5.1kAutomated safety check: PassMIT

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Questions about SEO Answer Visibility

What does SEO Answer Visibility do?

Observe answer visibility for approved buyer questions, audit discoverability and file evidence-backed improvement cards. SEO Answer Visibility is an agent skill from markfulton/ai-employees. Observe answer visibility for approved buyer questions, audit discoverability and file evidence-backed improvement cards.

How do I install SEO Answer Visibility in Claude Code?

Run `npx skills add markfulton/ai-employees --skill seo-answer-visibility -a claude-code`. Or copy the skill folder (employees/seo-employee/routines/seo-answer-visibility in markfulton/ai-employees) into .claude/skills/seo-answer-visibility in your project. Claude Code loads it when a task matches its description.

How do I install SEO Answer Visibility in Codex?

Run `npx skills add markfulton/ai-employees --skill seo-answer-visibility -a codex`. Or copy the skill folder (employees/seo-employee/routines/seo-answer-visibility in markfulton/ai-employees) into .agents/skills/seo-answer-visibility in your project. Codex loads it when a task matches its description.

Can I use SEO Answer Visibility in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add markfulton/ai-employees --skill seo-answer-visibility -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-answer-visibility, .gemini/skills/seo-answer-visibility, .github/skills/seo-answer-visibility and .opencode/skills/seo-answer-visibility in your project.

What does SEO Answer Visibility need to run?

Going by SKILL.md and its folder, SEO Answer Visibility needs the command-line tools its instructions call (node).

Does SEO Answer Visibility access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Answer Visibility safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Answer Visibility use?

SEO Answer Visibility is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Answer Visibility use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to SEO Answer Visibility?

Skills that share tags, products or a category with SEO Answer Visibility: Langsmith Observability (Orchestra-Research/AI-Research-SKILLs, 13k stars), Observability (BuilderIO/agent-native, 7.1k stars), Observability And Instrumentation (sickn33/agentic-awesome-skills, 47k stars) and Agent Observability (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Answer Visibility?

markfulton (a GitHub user) maintains it in markfulton/ai-employees, which has 495 GitHub stars. The repository holds 60 skills in this directory. The repository was last updated on October 7, 2026.

Source: markfulton/ai-employees on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.