Borrowing it
Nothing to install: this file belongs to prashishh/seo-geo-report-engine. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/prashishh/seo-geo-report-engine/main/.agents/skills/comparison-pages/SKILL.mdgit clone --depth 1 https://github.com/prashishh/seo-geo-report-engineWrote 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.
[](https://agentmods.dev/skills/prashishh/seo-geo-report-engine/comparison-pages)<a href="https://agentmods.dev/skills/prashishh/seo-geo-report-engine/comparison-pages"><img src="https://agentmods.dev/badge/skills/prashishh/seo-geo-report-engine/comparison-pages/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.
<a href="https://agentmods.dev/skills/prashishh/seo-geo-report-engine/comparison-pages"><img src="https://agentmods.dev/badge/skills/prashishh/seo-geo-report-engine/comparison-pages.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00162 | $0.01621 |
| Opus 5 | $0.00081 | $0.00811 |
| Sonnet 5 | $0.00032 | $0.00324 |
| Haiku 4.5 | $0.00016 | $0.00162 |
Grade A, and why
comparison-pages 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
comparison-pages
Build "us vs {competitor}" pages and a comparison/alternatives hub. These rank for
high-intent bottom-funnel queries and are disproportionately cited by AI answer engines,
so accuracy and fairness are non-negotiable — never fabricate a competitor fact. Shares the
generator and hub architecture with programmatic-seo; methodology in
playbooks/programmatic-seo.md. Methodology: PERCEIVE → ANALYZE → VALIDATE → ACT,
falsifiable claims. Today is 2026-06-23; write absolute dates.
Inputs
projects/<client>/client.yml— competitors list, domain, positioning, locale.- Existing research in
projects/<client>/research/.
Resolve context first: ./bin/mkt config show --project <client>.
Workflow
-
PERCEIVE — take the competitor set from
client.yml. Read thecompetitorslist (cross-check withmanagement-project-competitors/site-explorer-organic-competitorsif you need to find more). One page per "us vs {competitor}". -
ANALYZE — gather objective facts per competitor. For each one:
- Their positioning & top pages:
site-explorer-top-pages(what they're known for), andWebFetchtheir pricing / features / homepage for the primary source of truth. - Record only verifiable facts (features, pricing tiers, coverage, integrations, limits)
with the source URL. If a fact can't be confirmed, mark it
Unknown— do not guess.
- Their positioning & top pages:
-
VALIDATE — size demand (Ahrefs MCP, see
knowledge/ahrefs-mcp-map.md). Withkeywords-explorer-overview/-matching-terms, pull volume for"<competitor> alternative","<us> vs <competitor>","<competitor> vs <us>","<competitor> alternatives". Prune competitors with no demand; prioritize the rest by volume. -
ACT — build the comparison table. Structured, fair, fact-checked rows: the same attributes for both sides, each cell sourced. Be honest where the competitor wins — fairness is what makes the page (and your brand) credible and citable. Add a row-specific FAQ and Product / structured data (defer to the
schema-markupskill: Product, FAQPage, optionally a comparison/ItemList).
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.
- 11d ago First seen · 114 lines · 162 tokens per session scan A 8f40511fe16e
comparison-pages is a skill published in the GitHub repository prashishh/seo-geo-report-engine (5 stars, last pushed 2mo ago), licensed MIT. It adds 162 tokens to every session and 1,621 once invoked, about $0.0008 per session on Opus 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 2026-08-31.
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