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 agentmods add skills/planetscale/claude-plugin/10-customer-report-templatenpx skills add planetscale/claude-plugin --skill 10-customer-report-templategit clone --depth 1 https://github.com/planetscale/claude-pluginWrote 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/planetscale/claude-plugin/10-customer-report-template)<a href="https://agentmods.dev/skills/planetscale/claude-plugin/10-customer-report-template"><img src="https://agentmods.dev/badge/skills/planetscale/claude-plugin/10-customer-report-template.svg" alt="Measured on agentmods" 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 | $0.00027 | $0.01599 |
| Opus 5 | $0.00014 | $0.00800 |
| Sonnet 5 | $0.00005 | $0.00320 |
| Haiku 4.5 | $0.00003 | $0.00160 |
Grade A, and why
planetscale-customer-report-template 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 6d 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.
This is a copy
100% identical to planetscale-customer-report-template — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customer report template
Purpose
Produce a clear assessment report for a customer database and optional connected repository. The report should be actionable, evidence-backed, and safe. It should separate recommendations from applied changes.
Tone and framing
The report's purpose is an accurate assessment that helps the customer get full value from the platform they run. Feature adoption follows from evidence, never from framing. The register is technical and declarative — an engineer's assessment, not marketing copy.
- State unused features as capability gaps with quantified impact. Never write "off (good)", "not enabled (safe)", or otherwise present non-adoption as a positive finding. The correct form is: current state, what the feature provides, the measured finding it applies to. Example: "Raw query collection: disabled. Enabling it exposes literal parameter values per execution; applicable to Q1 (38% of total query time), where the pattern-level data is insufficient to isolate the triggering invocation."
- No enthusiasm markers. Do not use phrases like "earning its keep", "paying off", "easy to adopt", "cutting root-cause time from hours to minutes", or exclamation of any kind. State the mechanism and the measurement; let the numbers carry the argument.
- Operational costs are stated inline as facts, not softened: "literal values become visible to the observability pipeline" is a property of the feature, stated once, without reassurance.
- Every recommendation cites the specific finding it addresses — fingerprint, metric, event count, time window. A recommendation without a measurement attached is incomplete.
- Active features are assessed, not praised. If a feature is enabled, report what it is currently doing in measurable terms ("anomaly detection flagged the connection spike 9 times in 7 days; no delivery channel is configured") and whether its configuration is complete.
- Fit is part of the analysis: if the evidence does not support a feature for this customer, state that.
- Recommendations are framed by what the change provides, not by the threat of the current state. Write "a dedicated application role scopes credentials per service and enables rotation without downtime", not "limits the blast radius of credential compromise". Avoid dramatizing vocabulary: "blast radius", "unprotected", "exposed", "public-by-default", "at risk". Real risks are still stated, as facts — "the production branch runs zero replicas; recovery from a primary failure requires a restore" is a finding and belongs in the report. What is excluded is dramatization, not disclosure.
- Platform behavior is reported with verified semantics, not assumptions. When two API surfaces show different values, they are usually distinct settings — check the documentation and report the effective state. Do not label platform behavior inconsistent, contradictory, or buggy on an unverified assumption. If the semantics cannot be verified, state what each surface reports without drawing a conclusion and direct the question to PlanetScale support. If verified platform behavior is actually wrong, report it factually and route it to PlanetScale support — it is a platform issue, not a customer configuration finding.
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.
- 6d ago First seen · 219 lines · 27 tokens per session scan A b45921eb63cc
planetscale-customer-report-template is a skill published in the GitHub repository planetscale/claude-plugin (4 stars, last pushed 5d ago), licensed Apache-2.0. It adds 27 tokens to every session and 1,599 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to planetscale-customer-report-template, differing in 0 lines, and is treated as a copy.
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