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/disler/pi-agent-observability/htmlvspecnpx skills add disler/pi-agent-observability --skill htmlvspecgit clone --depth 1 https://github.com/disler/pi-agent-observabilityWrote 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/disler/pi-agent-observability/htmlvspec)<a href="https://agentmods.dev/skills/disler/pi-agent-observability/htmlvspec"><img src="https://agentmods.dev/badge/skills/disler/pi-agent-observability/htmlvspec.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 | $0.00119 | $0.04794 |
| Opus 5 | $0.00060 | $0.02397 |
| Sonnet 5 | $0.00024 | $0.00959 |
| Haiku 4.5 | $0.00012 | $0.00479 |
Grade A, and why
htmlvspec 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 3d 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 — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
htmlvspec
Purpose
Produce a visual engineering implementation plan as one self-contained HTML page —
specs/<plan-name>.html — that you can open directly in a browser. The plan is authored
directly in HTML using the template below, with one AI-generated diagram image per
section (hero + per major H2) generated in parallel and embedded inline, and a dedicated
Freeform zone that lets you author any HTML you want (interactive toggles, animated SVG
flows, comparison matrices, decision trees, etc.) to make the plan clearer and richer than
prose could.
Phases, in order:
- Plan phase — analyze, explore, design (same thinking as a normal spec).
- HTML authoring phase — write the plan into the HTML Plan Template.
- Image phase — generate one diagram per section in parallel and embed them inline.
- Freeform phase — enrich the page with custom HTML per the Freeform Instruction Set.
Variables
USER_PROMPT: $1
ALL_ARGUMENTS: $ARGUMENTS
PLAN_OUTPUT_DIRECTORY: specs/
PLAN_SLUG: kebab-case name derived from the plan topic (e.g. in-memory-ttl-lru-cache)
HTML_OUTPUT: specs/htmlvspec-<PLAN_SLUG>.html — the filename MUST always begin with the htmlvspec- prefix
IMAGE_DIR: specs/htmlvspec-<PLAN_SLUG>/ — sibling directory matching the HTML filename (same htmlvspec- prefix)
IMAGE_GENERATOR: ~/.claude/skills/htmlvspec/scripts/generate_image.py
IMAGE_SIZE: 2048x1152 (wide 16:9 by default)
IMAGE_QUALITY: high
HERO_IMAGE_NAME: 00-hero.png
MAX_TEXT_LABELS_PER_IMAGE: 10
MAX_TOTAL_IMAGES: 10
Instructions
Plan phase
- IMPORTANT: If no
USER_PROMPTis provided, stop and ask the user to provide it. - Carefully analyze the USER_PROMPT. Determine task type (chore|feature|refactor|fix|enhancement) and complexity (simple|medium|complex).
- Think deeply (ultrathink) about the best implementation approach.
- Explore the codebase to understand existing patterns and architecture.
- Decide which sections from the HTML Plan Template apply (include the conditional sections only when task type/complexity warrants them, exactly like a normal spec).
- Generate a descriptive kebab-case PLAN_SLUG from the topic.
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.
- 3d ago First seen · 303 lines · 119 tokens per session scan A ee3414ce2ab2
htmlvspec is a skill published in the GitHub repository disler/pi-agent-observability (142 stars, last pushed 3mo ago), licensed MIT. It adds 119 tokens to every session and 4,794 once invoked, about $0.0006 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.
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