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/hekivo/superpowers-sage/wp-phpstannpx skills add hekivo/superpowers-sage --skill wp-phpstangit clone --depth 1 https://github.com/hekivo/superpowers-sageWrote 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/hekivo/superpowers-sage/wp-phpstan)<a href="https://agentmods.dev/skills/hekivo/superpowers-sage/wp-phpstan"><img src="https://agentmods.dev/badge/skills/hekivo/superpowers-sage/wp-phpstan.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 | $0.00090 | $0.02070 |
| Opus 5 | $0.00045 | $0.01035 |
| Sonnet 5 | $0.00018 | $0.00414 |
| Haiku 4.5 | $0.00009 | $0.00207 |
Grade A, and why
superpowers-sage:wp-phpstan 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.
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Static Analysis for Sage/Acorn with PHPStan
When to use
- Setting up static analysis on a Sage theme for the first time
- Adding PHPStan to an existing project and managing the baseline
- Fixing type errors reported by PHPStan in Sage/Acorn code
- Configuring CI pipelines to enforce static analysis
- Incrementally raising the PHPStan analysis level
Inputs required
- Current PHPStan level (if already configured), or confirmation this is a fresh setup
- Whether Larastan and WordPress stubs are already installed
- Target analysis level (or follow the recommended progression)
- CI platform in use (GitHub Actions, GitLab CI, etc.) if configuring CI integration
Procedure
1. Install dependencies
lando theme-composer require --dev phpstan/phpstan larastan/larastan szepeviktor/phpstan-wordpress
This installs:
- phpstan/phpstan — the core static analysis engine
- larastan/larastan — Laravel-specific extensions (facades, models, service container, Eloquent)
- szepeviktor/phpstan-wordpress — WordPress function stubs and type definitions
2. Configure phpstan.neon
Create or update phpstan.neon in the theme root:
includes:
- vendor/larastan/larastan/extension.neon
- vendor/szepeviktor/phpstan-wordpress/extension.neon
parameters:
paths:
- app/
level: 0
# WordPress dynamic functions that PHPStan cannot resolve
ignoreErrors:
- '#Function apply_filters invoked with#'
- '#Function do_action invoked with#'
- '#Function add_filter expects#'
- '#Function add_action expects#'
# Scan files for WordPress global function definitions
scanDirectories:
- vendor/szepeviktor/phpstan-wordpress/bootstrap.php
# Treat Acorn facades correctly via Larastan
checkGenericClassInNonGenericObjectType: false
3. Run the initial analysis
lando theme-composer exec phpstan -- analyse
At level 0, this should produce few or no errors. If errors exist, fix them or generate a baseline.
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 · 254 lines · 90 tokens per session scan A bc3301d870aa
superpowers-sage:wp-phpstan is a skill published in the GitHub repository hekivo/superpowers-sage (13 stars, last pushed 2mo ago), licensed MIT. It adds 90 tokens to every session and 2,070 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 2026-08-30.
Other skills, from other repositories
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
systematic-debugging
Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.
diagnose
Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.
azsdk-common-pipeline-analysis
Analyze Azure SDK CI/CD pipeline failures into a structured diagnosis, and define the required output format. Load this skill before calling azsdkanalyzepipeline, which returns raw failure data that this skill interprets and formats. USE FOR: "pipeline failed", "build failure", "CI check failing", "tests failing in…
repro-admin
Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…