Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/siddiqss/semantic-seo-suitenpx agentmods add skills/siddiqss/semantic-seo-suite/seo-performance-trackerWrote 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/siddiqss/semantic-seo-suite/seo-performance-tracker)<a href="https://agentmods.dev/skills/siddiqss/semantic-seo-suite/seo-performance-tracker"><img src="https://agentmods.dev/badge/skills/siddiqss/semantic-seo-suite/seo-performance-tracker/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/siddiqss/semantic-seo-suite/seo-performance-tracker"><img src="https://agentmods.dev/badge/skills/siddiqss/semantic-seo-suite/seo-performance-tracker.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 | $0.00108 | $0.00842 |
| Opus 5 | $0.00054 | $0.00421 |
| Sonnet 5 | $0.00022 | $0.00168 |
| Haiku 4.5 | $0.00011 | $0.00084 |
Grade A, and why
seo-performance-tracker 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 10d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seo-performance-tracker
The measured feedback loop. It replaces guesswork (and the fabricated "Pillar Page Rank"
that wrapper tools invent) with real Search Console data joined to the topical map. Every
figure is measured (GSC) or derived (rollups) — never estimated.
Read first: ../../framework/topical-map-theory.md (pillars/priority),
../../framework/query-semantics.md (query networks → new nodes).
Preconditions
topical-map.jsonwithurls on published nodes (the auditor sets these).- GSC configured:
grounding.sources.gsc: true+credentials.gsc_credentials_path. If not configured, say so and do NOT invent metrics — spot-checking positions via web_search is unreliable; be explicit about that limitation.
Workflow
-
Pull GSC data:
python ../../scripts/gsc_client.py --site "<property>" --creds <path> \ --start <date> --end <date> --dims query,page \ --out brands/<slug>/data/gsc/pull.json # optional prior period for decay: python ../../scripts/gsc_client.py ... --start <earlier> --end <earlier> \ --out brands/<slug>/data/gsc/prev.json -
Analyse against the map:
python ../../scripts/gsc_analyze.py --gsc brands/<slug>/data/gsc/pull.json \ [--gsc-prev brands/<slug>/data/gsc/prev.json] \ --map brands/<slug>/topical-map.json --brand "<Brand>" \ --out brands/<slug>/audits/<date>-performance.mdProduces:
- Pillar rollups — impressions/clicks/avg-position per pillar (
derived). The honest Pillar Page Rank. - Striking-distance — queries at position 5–15 → quick-win update targets.
- Measured cannibalization — one query landing on multiple pages (the strongest cannibalization signal; confirms/ː refutes the auditor's embedding guess).
- Decaying pages — >30% click loss vs the prior period.
- Uncovered queries — GSC queries not in any node's query network → candidate new map nodes.
- Pillar rollups — impressions/clicks/avg-position per pillar (
-
Feed the loop:
- Add uncovered-query candidates to the map via topical-map-builder (as new nodes or as query-network additions to existing nodes).
- Mark striking-distance and decaying nodes
needs-update; push them upcalendar.md. - Send confirmed measured-cannibalization pairs to semantic-site-auditor / linking-and-schema for consolidation/redirect.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 74 lines · 108 tokens per session scan A 4aa937ed0eb4
seo-performance-tracker is a skill published in the GitHub repository siddiqss/semantic-seo-suite (8 stars, last pushed 2mo ago), licensed MIT. It adds 108 tokens to every session and 842 once invoked, about $0.0005 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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