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 pjt222/agent-almanac --skill assess-formgit clone --depth 1 https://github.com/pjt222/agent-almanacWrote 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/pjt222/agent-almanac/assess-form)<a href="https://agentmods.dev/skills/pjt222/agent-almanac/assess-form"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/assess-form/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/pjt222/agent-almanac/assess-form"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/assess-form.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 54 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00086 | $0.03137 |
| Opus 5.5 | $0.00034 | $0.01255 |
| Sonnet 5.5 | $0.00017 | $0.00627 |
| Haiku 4.5 | $0.00009 | $0.00314 |
Grade A, and why
assess-form 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 1mo 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 — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assess Form
Evaluate a system's current structural form — its architecture, rigidity, pressure points, and capacity for change — to determine transformation readiness before initiating metamorphosis.
When to Use
- Before any significant architectural change to understand the starting point
- When a system feels "stuck" but the reasons are unclear
- When external pressure (growth, market shift, tech debt) is mounting but the response is uncertain
- Assessing whether a proposed transformation is feasible given the current form
- Periodic health checks for long-lived systems (annual form assessment)
- Complementing
adapt-architecture— assess first, then transform
Inputs
- Required: The system to assess (codebase, organization, infrastructure, process)
- Optional: Proposed transformation direction (what might the system need to become?)
- Optional: Known pain points or pressure sources
- Optional: Previous transformation attempts and their outcomes
- Optional: Time horizon for potential transformation
- Optional: Available resources for transformation effort
Procedure
Step 1: Inventory the Current Form
Catalog the system's structural elements without judgment — understand what exists before evaluating it.
- Map the structural components:
- Modules: distinct functional units (services, teams, packages, departments)
- Interfaces: how modules connect (APIs, protocols, contracts, reporting lines)
- Data flows: how information moves through the system
- Dependencies: what depends on what (direct, transitive, circular)
- Load-bearing structures: components that everything else relies on
- Document the form's age and history:
- When was each major component introduced?
- Which components have changed recently vs. remained static?
- What is the "geological layer" structure (old core, newer additions, recent patches)?
- Identify the form's "skeleton" vs. "flesh":
- Skeleton: structural decisions that are costly to change (language, database, deployment model)
- Flesh: functional decisions that can change more easily (business logic, UI, configuration)
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.
- 1mo ago First seen · 245 lines · 86 tokens per session scan A 053792f7ada2
assess-form is a skill published in the GitHub repository pjt222/agent-almanac (42 stars, last pushed 5d ago), licensed MIT. It adds 86 tokens to every session and 3,137 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-03.
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init-workspace
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product-audit
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review-change
Review a change with only applicable internal axes, classify every finding, persist fix-now work, and return one evidence-backed decision. Findings only; --adversarial N uses isolated reviewers; --synthesize fuses supplied reviewer tables. Triggers: "review-change", "review this change", "adversarial review".