Agent skill

Local Pack Audit

by unifapi-agent in unifapi-agent/agents

When a local business wants to know where it ranks in Google's local pack / map results for its key queries — in one location or across many.

MITAuto-check passedMarketing & SEO

Install Local Pack Audit

skills CLI
$ npx skills add unifapi-agent/agents --skill local-pack-audit -a claude-code

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

GitHub CLI
$ gh skill install unifapi-agent/agents local-pack-audit --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/unifapi-agent/agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/local-seo-agent/local-pack-audit .claude/skills/local-pack-audit && 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
local-pack-audit
GitHub stars
587
Token cost
~2.4k tokens
SKILL.md length
1,073 words
Files
3 (incl. references)
Skills in repo
47
Repo updated
First seen
Licence
MIT

At a glance

When a local business wants to know where it ranks in Google's local pack / map results for its key queries — in one location or across many.

  • Works in 6 steps: Define queries and locations — required.… → Set the proximity baseline. The pack… → Pull the live pack for each query ×… → …
  • Tasks that involve Local SEO
  • SKILL.md covers Use UnifAPI for live evidence, Workflow, Output: rank grid + findings and Guardrails, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Local Pack Audit is an agent skill from unifapi-agent/agents. When a local business wants to know where it ranks in Google's local pack / map results for its key queries — in one location or across many. Also use on "local pack ranking," "am I in the map pack," "where do I rank on Google Maps," "local SERP audit," "rank tracking by location," "multi-location local SEO," or "why aren't we showing up locally." Reads public map and SERP data only — read-only research.

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `README.md` and `references/methodology.md`).

It sits in Marketing & SEO, covering Local SEO. It works with Google Maps Platform. The repository describes itself as: Open-source marketing agents for Claude, ChatGPT, Codex, OpenClaw & Hermes. One plugin: SEO audits, GEO / AI-visibility, local SEO, KOL pricing, social listening & competitive… The licence is MIT.

When your agent uses it

  • Tasks that involve Local SEO

Example prompts

  • “local pack ranking,”
  • “am I in the map pack,”
  • “where do I rank on Google Maps,”
  • “/local-pack-audit”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Define queries and locations — required. Take the business's priority queries (e.g. "emergency plumber Austin", "24 hour plumber") and the…
  2. Set the proximity baseline. The pack re-ranks by distance to the searcher, so the exact point you search from changes the result. For each…
  3. Pull the live pack for each query × location pairing via local/search + maps/search, looping the location param. Record who ranks 1–3…
  4. Score each cell with the rubric below so the grid sorts by opportunity, not alphabet.
  5. Attribute each gap to proximity, prominence, or relevance (see below). For a relevance/prominence gap, pull the winner's…
  6. Find the pattern. Where does the business rank well, where does it fall out of the pack, and (for multi-location) which branches lag the…

What it can do on your machine

Read from SKILL.md and the folder at commit fb53247. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    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

Local Pack Audit loads about 2.4k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 106 tokens; SKILL.md has 1,073 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~106
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

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 unifapi-agent/agents at commit fb53247, republished under its MIT licence (© unifapi-agent). 1,073 words, ~2,410 tokens.

Download SKILL.mdSave it as .claude/skills/local-pack-audit/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
local-pack-audit
description
When a local business wants to know where it ranks in Google's local pack / map results for its key queries — in one location or across many. Also use on "local pack ranking," "am I in the map pack," "where do I rank on Google Maps," "local SERP audit," "rank tracking by location," "multi-location local SEO," or "why aren't we showing up locally." Reads public map and SERP data only — read-only research.
license
MIT
metadata.author
UnifAPI
metadata.version
1.0.0

Local Pack Audit

You are a local-search analyst. The local pack — the three-business map block at the top of a "near me" search — is where most local clicks go. This skill pulls the live local pack / map results for a business's target queries and reports exactly where it ranks against the businesses above it: for one location, or the same queries across many.

This is an enhanced skill: it reads live public data through UnifAPI.

Use UnifAPI for live evidence

A local rank is personalized and proximity-weighted — you cannot reason about it from memory, you have to pull the actual pack for the actual query at the actual search point. Use the unifapi skill to connect (OAuth MCP), then call:

  • Local pack positions — local/search, maps/search — for each query × location, the businesses occupying the pack and their position. Loop the location param to build the grid: re-run the same query from each city / branch / proximity point. Each result carries name, place_id, rating, review_count, category, address, phone, website, hours — everything you need to profile who sits above the target. Tie the target to its place_id, not its name.
  • Blended local SERP — seo/serp — who ranks the organic local results for the same query. A business can hold the organic blue links yet be absent from the pack (an eligibility/category gap, not invisibility) — keep the two distinct. Also confirms whether the pack the maps endpoints return matches the live SERP block.
  • Competitor local landing page — seo/competitors/relevant-pages — for a rival outranking the target, its top organic pages reveal the local landing page (city/service page) doing the relevance work behind its pack slot.

UnifAPI reads public data only — it never touches the business's Google Business Profile. Keep any billing metadata so the output can state record cost.

Workflow

  1. Define queries and locations — required. Take the business's priority queries (e.g. "emergency plumber Austin", "24 hour plumber") and the location(s) to check — one storefront, or every city/branch for a multi-location operator. If queries are missing, ask; do not guess the keyword set. (Read .agents/product-marketing.md / .claude/product-marketing.md first if it exists.)
  2. Set the proximity baseline. The pack re-ranks by distance to the searcher, so the exact point you search from changes the result. For each location pass a precise location to local/search / maps/search: at minimum the city centroid; for a storefront, prefer coordinates at the address. Note the search point, language, and device with every position — a rank measured 8km away is not the same finding as one at the door.
  3. Pull the live pack for each query × location pairing via local/search + maps/search, looping the location param. Record who ranks 1–3 (plus extended "More places" results where available) and the target's position — or its absence. Capture place_id, name, rating, review_count, category for every business in the pack. Cross-check the organic block with seo/serp.
  4. Score each cell with the rubric below so the grid sorts by opportunity, not alphabet.
  5. Attribute each gap to proximity, prominence, or relevance (see below). For a relevance/prominence gap, pull the winner's seo/competitors/relevant-pages to see the local page it ranks.
  6. Find the pattern. Where does the business rank well, where does it fall out of the pack, and (for multi-location) which branches lag the others on the same query? Separate proximity-explained gaps from prominence/relevance gaps.
Cell scoring rubric

Score every query × location cell so the grid sorts by opportunity:

Cell stateScoreMeaning
Target in position 15Defend
Target in position 2–34Hold / push to 1
Target in extended "More places" (4–10)2Within striking distance
Target absent but ranks organically1Pack-eligibility gap, not invisibility
Target absent entirely0Investigate category/proximity/relevance

Opportunity = (5 − score) × query priority weight. Rank cells by opportunity descending; the top of that list is where work moves the needle.

Show full SKILL.md (448 more words)Show less
Reading the three ranking factors

When the target underperforms, attribute the gap to one of Google's three local factors so the operator knows what to fix:

  • Proximity — does rank improve as the search point nears the address, and is the winner simply closer? Then the cell is proximity-bound; a single storefront can't out-rank a closer rival, but service-area or category breadth can widen the radius.
  • Prominence — do the businesses above the target carry markedly higher review_count / rating? Prominence gaps are the most actionable: review velocity and citations.
  • Relevance — does the winner's primary category or name match the query more exactly, or does its seo/competitors/relevant-pages show a dedicated local landing page? A relevance gap points at category/listing/content fixes (hand off to listing-accuracy-audit).

Full method, edge cases, and the multi-location pattern read are in references/methodology.md.

Output: rank grid + findings

markdown
# Local Pack Audit — <business> — <date>

Search params: location(s) <…> · language <…> · device <…>

## Rank grid (one row per query × location)

| Query             | Location (search point)       | Target position | Cell score | Above target (name · rating · reviews · category) | Likely factor |
| ----------------- | ----------------------------- | --------------- | ---------- | ------------------------------------------------- | ------------- |
| emergency plumber | Austin TX (downtown centroid) | 2               | 4          | Joe's Plumbing · 4.8 · 412 · Plumber              | Prominence    |
| 24 hour plumber   | Austin TX (centroid)          | not in pack     | 0          | A1 Drain · 4.6 · 290 · Emergency plumber service  | Relevance     |

## Findings

- Top opportunities, ranked by opportunity score (highest-impact cells first).
- Multi-location: a location × query matrix flagging which branches are missing from or buried in the pack on the same query.
- Each competitor above the target annotated with rating, review count, category, and the factor that explains the gap.
- Record cost consumed (or best estimate if billing metadata is unavailable).
Worked example

Brief: a 2-location HVAC company, queries "ac repair" and "furnace repair", locations Austin + Round Rock.

  • "ac repair" × Austin → target position 2 (score 4); winner Cool Air has 4.9 / 680 reviews vs. target 4.7 / 210 → prominence gap, review velocity.
  • "ac repair" × Round Rock → target position 1 (score 5) → defend.
  • "furnace repair" × Austin → target absent (score 0) but ranks #4 organically on seo/serp (score 1, not 0); winners all carry "Furnace repair service" as primary category and their seo/competitors/relevant-pages shows a dedicated furnace page → relevance gap, hand to listing-accuracy-audit.

Verdict: the Austin furnace cell is the single highest-opportunity fix (category + landing page), Austin AC is a review-volume play, Round Rock is healthy. Reads: 8 local/maps + 4 SERP + 2 relevant-pages.

Guardrails

  • Read-only ("eyes, not hands"). Public data only. It reports rankings; it never edits a Google Business Profile, posts, or submits anything. The operator's own team makes any listing or content changes.
  • Confirmed vs inferred. Report the exact search point, language, device, and timestamp each position was measured at. Label positions read off the pack as confirmed and the proximity/prominence/relevance attribution as inferred; if the data doesn't support an attribution, label the cell "unattributed" rather than guessing.
  • Dated snapshots, re-runnable. Rankings are personalized and time-sensitive — treat each pull as a snapshot, not a guarantee; keep the query × location watchlist so the grid can be re-run for a trend.
  • Pack membership ≠ organic rank. A business can rank organically yet be absent from the pack (category/eligibility), or vice versa — keep the two measurements distinct.

References

  • references/methodology.md — full grid method, proximity sampling, the three-factor attribution checklist, and multi-location pattern reading.
  • listing-accuracy-audit (Local SEO): checks whether the business's own listing details are correct and complete — usually the fix behind a relevance gap.
  • local-competitor-scan (Local SEO): profiles the competitors winning these local-pack slots.
  • unifapi: the shared data skill — connect MCP and discover the operations above.

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

Files

SKILL.md and 2 other files (references) in skills/local-seo-agent/local-pack-audit of unifapi-agent/agents.

  • SKILL.md
  • README.md
  • references/methodology.md

Open the folder on GitHubat commit fb53247

Compare with similar skills

Local Pack Audit 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.

Local Pack Audit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Local Pack Audit this skillunifapi-agent/agents587—~2.4kAutomated safety check: PassMIT
Google Mapscablate/mcp-google-map468—~909Automated safety check: PassMIT
Google Maps Local SEOcablate/mcp-google-map468—~633Automated safety check: PassMIT
Google Maps Travel Planningcablate/mcp-google-map468—~710Automated safety check: PassMIT
Maps Intelligence for Local SEOAgriciDaniel/claude-seo18k1 repos~3.1kAutomated safety check: PassMIT
Local SEOnowork-studio/notfair-plugin3.9k—~1.6kAutomated safety check: PassMIT

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Categories

Questions about Local Pack Audit

What does Local Pack Audit do?

When a local business wants to know where it ranks in Google's local pack / map results for its key queries — in one location or across many. Local Pack Audit is an agent skill from unifapi-agent/agents. When a local business wants to know where it ranks in Google's local pack / map results for its key queries — in one location or across many.

When should I use Local Pack Audit?

Local Pack Audit fits situations like: tasks that involve Local SEO.

How do I install Local Pack Audit in Claude Code?

Run `npx skills add unifapi-agent/agents --skill local-pack-audit -a claude-code`. Or copy the skill folder (skills/local-seo-agent/local-pack-audit in unifapi-agent/agents) into .claude/skills/local-pack-audit in your project. Claude Code loads it when a task matches its description.

How do I install Local Pack Audit in Codex?

Run `npx skills add unifapi-agent/agents --skill local-pack-audit -a codex`. Or copy the skill folder (skills/local-seo-agent/local-pack-audit in unifapi-agent/agents) into .agents/skills/local-pack-audit in your project. Codex loads it when a task matches its description.

Can I use Local Pack Audit 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 unifapi-agent/agents --skill local-pack-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/local-pack-audit, .gemini/skills/local-pack-audit, .github/skills/local-pack-audit and .opencode/skills/local-pack-audit in your project.

What does Local Pack Audit need to run?

SKILL.md names no scripts, command-line tools or credentials: Local Pack Audit is instructions for the agent only.

Does Local Pack Audit 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 Local Pack Audit 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 Local Pack Audit use?

Local Pack Audit is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Local Pack Audit use?

About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.7k tokens, read only when the agent opens those files.

What are the alternatives to Local Pack Audit?

Skills that share tags, products or a category with Local Pack Audit: Google Maps (cablate/mcp-google-map, 468 stars), Google Maps Local SEO (cablate/mcp-google-map, 468 stars), Google Maps Travel Planning (cablate/mcp-google-map, 468 stars) and Maps Intelligence for Local SEO (AgriciDaniel/claude-seo, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Local Pack Audit?

unifapi-agent (a GitHub organization) maintains it in unifapi-agent/agents, which has 587 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on September 5, 2026.

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