negative-keyword-sweep

negative-keyword-sweep is a skill for Claude Code from markifact/markifact-mcp. It costs 56 tokens per session (1,514 once invoked), scanned A, original, MIT.

A Google Ads search-term cleanup workflow that finds searches spending money without useful results and adds them as negative keywords. Negative keywords stop an advert from appearing for matching searches.

In plain words
What is it for?
Use it to review search-term reports, find no-conversion or low-conversion searches and unwanted intent such as jobs or free, and add negatives with suitable match types.
Why use it?
It reduces wasted search-ad spend while choosing account, campaign, or ad-group scope so useful searches are less likely to be blocked.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the markifact plugin — 10 skills, 7 commands, 1 agent, 1 MCP server shipped together

Good fit Use it to review search-term reports, find no-conversion or low-conversion searches and unwanted intent such as jobs or free, and add negatives with suitable match types.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/markifact/markifact-mcp/negative-keyword-sweep
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add markifact/markifact-mcp --skill negative-keyword-sweep
Clone the repo
git clone --depth 1 https://github.com/markifact/markifact-mcp

Made for: Claude Code.

Or install markifact, the plugin that ships this one along with the rest of its 10 skills, 7 commands, 1 agent, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for negative-keyword-sweep

README.md
[![agentmods](https://agentmods.dev/badge/skills/markifact/markifact-mcp/negative-keyword-sweep/github.svg)](https://agentmods.dev/skills/markifact/markifact-mcp/negative-keyword-sweep)
Your own site
<a href="https://agentmods.dev/skills/markifact/markifact-mcp/negative-keyword-sweep"><img src="https://agentmods.dev/badge/skills/markifact/markifact-mcp/negative-keyword-sweep/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for negative-keyword-sweep

Your own site · 80×15
<a href="https://agentmods.dev/skills/markifact/markifact-mcp/negative-keyword-sweep"><img src="https://agentmods.dev/badge/skills/markifact/markifact-mcp/negative-keyword-sweep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,514 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00056 $0.01514
Opus 5.5 $0.00022 $0.00606
Sonnet 5.5 $0.00011 $0.00303
Haiku 4.5 $0.00006 $0.00151

Measured 27d ago against content hash e434d34c5a27, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

negative-keyword-sweep scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 27d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/hermes/markifact/skills/negative-keyword-sweep/SKILL.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Goal

Pull the search-terms report, identify spend that isn't producing, group it intelligently, and add negatives at the right level — without nuking legitimate intent.

Inputs to confirm (batch)

  1. Account name (substring) — required.
  2. Scope — single campaign, list of campaigns, or "all Search campaigns" — required.
  3. Lookback — default 30 days; user can override (60 / 90).
  4. Waste thresholds — defaults; allow override:
    • No-converter: spend ≥ $X over lookback AND 0 conversions. Default $X = 2× target CPA, or $50 if no target.
    • Low-CVR offender: spend ≥ 3× target CPA AND CVR < 25% of account CVR.
    • Off-brand / off-intent: terms that match a denylist of words (e.g. free, jobs, careers, tutorial, review, salary, download, cheap, pirate, crack) — calibrated to vertical.
  5. Negative scope preference — default behavior:
    • Recurring junk seen across multiple campaigns → account-level shared negative list.
    • Waste seen only in one campaign → campaign-level.
    • Single-theme misintent (e.g. "free" only hurts a paid product ad group) → ad-group-level.
    • Default match type: phrase, except for single-word obvious junk → broad isn't an option (negatives have no broad), so use exact for single tokens like free.

Workflow

  1. Discover ops: gads_select_accounts, gads_list_report_fields, gads_get_report, gads_create_negative_keyword_list, gads_attach_negative_list_to_campaigns, gads_add_keywords_to_negative_list, gads_add_negative_keywords_to_campaigns, gads_add_negative_keywords_to_ad_groups.
  2. Inspect every op via get_operation_inputs.
  3. Resolve account (substring).
  4. Pull search-terms report via gads_get_report at the search-term granularity (search_term_view resource). Required fields: search_term, campaign_id/name, ad_group_id/name, impressions, clicks, cost, conversions, conv_value, ctr, cvr.
  5. Compute baselines: account-level CVR over lookback. Compute target CPA if not given (use account history / average across the scope).
  6. Apply thresholds → candidate list. Tag each candidate with the trigger reason (no-conv, low-CVR, denylist).
  7. Cluster candidates by intent. Group on shared roots / themes (e.g. free trial spreadsheet, free template excel, free download → cluster "free*"). For each cluster, propose:
    • Negative keyword(s) (the minimum tokens needed to block the cluster — usually a phrase).
    • Match type (phrase by default; exact for single-token denylist hits; phrase for multi-word patterns).
    • Scope (account / campaign / ad-group) per the rules above.
  8. Build a preview table showing every proposed negative with: keyword, match, scope, target campaigns/ad groups, wasted spend that would have been blocked, and a sample of 1–3 search terms it covers. Wait for user confirmation.
  9. Execute:
    • Account-level batch → if a list with the right purpose already exists, use gads_add_keywords_to_negative_list. If not, gads_create_negative_keyword_list then gads_add_keywords_to_negative_list then gads_attach_negative_list_to_campaigns.
    • Campaign-level batch → gads_add_negative_keywords_to_campaigns.
    • Ad-group-level batch → gads_add_negative_keywords_to_ad_groups.
  10. Confirm: count by scope, total estimated spend blocked.

Read the full file on GitHub · 82 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 27d ago First seen · 82 lines · 56 tokens per session scan A e434d34c5a27

Subscribe to this mod's changes

negative-keyword-sweep is a skill published in the GitHub repository markifact/markifact-mcp (52 stars, last pushed 13d ago), licensed MIT. It adds 56 tokens to every session and 1,514 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.

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