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.
npx skills add acamolese/google-search-console-mcp --skill gsc-content-opportunitiesgit clone --depth 1 https://github.com/acamolese/google-search-console-mcpWrote 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/acamolese/google-search-console-mcp/gsc-content-opportunities)<a href="https://agentmods.dev/skills/acamolese/google-search-console-mcp/gsc-content-opportunities"><img src="https://agentmods.dev/badge/skills/acamolese/google-search-console-mcp/gsc-content-opportunities/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/acamolese/google-search-console-mcp/gsc-content-opportunities"><img src="https://agentmods.dev/badge/skills/acamolese/google-search-console-mcp/gsc-content-opportunities.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 | $0.00062 | $0.00538 |
| Opus 5 | $0.00031 | $0.00269 |
| Sonnet 5 | $0.00012 | $0.00108 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
gsc-content-opportunities 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 12d 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.
What it actually says
Content opportunities
1. Gather
Run all four with period="last_3_months":
gsc_quick_wins— queries close enough to the top that a push pays offgsc_ctr_gapswithentity="page"— pages that rank but are not clickedgsc_cannibalization— queries split across several pagesgsc_content_decaywithmonths=6— pages sliding down month after month
They answer different questions and the plan needs all four. Decay in particular is invisible to any period comparison: a page that halves over six months never shows a sharp drop in any single month.
2. Sort the work into four buckets
- Rewrite (from
ctr_gaps): the ranking is already there, the snippet is not earning the click. Cheapest work on the list. Quote the current CTR against the expected one. - Strengthen (from
quick_wins): queries just off the first page. Quote the estimated uplift, which is the clicks the query would earn at position 3. - Merge or re-point (from
cannibalization): name the page that should win. - Refresh (from
content_decay): quote the peak month and the last month so the decline is visible.
3. Rank and state the limits
Order the whole plan by estimated click gain, not by bucket. Then state the thresholds the tools applied — every response's meta line carries them — so the reader knows what was filtered out. On a small property the floors do most of the filtering.
Two things to be honest about:
- The uplift figures assume the page reaches the target position. They size the opportunity; they are not a forecast.
themesoutput, where you use it, is word frequency across queries. It is a starting point for topic ideas, not evidence of demand.
4. Optional
If the user wants the plan as a document rather than a message, gsc_audit
produces a self-contained HTML report covering the same ground plus the
technical issues.
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.
- 12d ago First seen · 51 lines · 62 tokens per session scan A 567af7bf8b32
gsc-content-opportunities is a skill published in the GitHub repository acamolese/google-search-console-mcp (8 stars, last pushed 20d ago), licensed MIT. It adds 62 tokens to every session and 538 once invoked, about $0.0003 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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