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/xobotyi/cc-foundry/alignmentnpx skills add xobotyi/cc-foundry --skill alignmentgit clone --depth 1 https://github.com/xobotyi/cc-foundryWrote 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/xobotyi/cc-foundry/alignment)<a href="https://agentmods.dev/skills/xobotyi/cc-foundry/alignment"><img src="https://agentmods.dev/badge/skills/xobotyi/cc-foundry/alignment.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 | $0.00045 | $0.02877 |
| Opus 5 | $0.00023 | $0.01438 |
| Sonnet 5 | $0.00009 | $0.00575 |
| Haiku 4.5 | $0.00005 | $0.00288 |
Grade A, and why
alignment 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 yesterday.
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 — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alignment
Declare every pattern you intend to follow and every design opinion you've formed — explicitly, with evidence and reasoning — so the human can correct them before implementation begins. Research produces facts; alignment is where you form and surface opinions for correction.
Prerequisites
Locate the inputs:
- Brief — check conversation context first; fall back to
design-docs/NN-name.brief.md; if absent, ask whether to run discovery. - Research — check conversation context first; fall back to
design-docs/NN-name.research.md; if absent, ask whether to run research. - Glossary — load
docs/glossary.mdif present. If absent (first iteration), schedule creation at Phase 3 end (see Glossary maintenance below).
Process
Phase 1 — Synthesize
- Read the brief, research, and glossary (if present).
- From research, extract:
- Codebase patterns with prevalence (dominant convention vs isolated instance).
- Integration points and boundaries relevant to the brief's goals.
- From the brief, extract:
- Motivation, desired end state, constraints, non-goals.
- Flagged term ambiguities — unresolved terms discovery surfaced for alignment to resolve.
- Not-yet-specified items — unknowns discovery could not yet phrase as precise questions. Check each against the research findings: graduate the ones research has sharpened into open questions for Phase 3; carry the rest into the alignment document unchanged.
- From the glossary, extract:
- Canonical vocabulary to use throughout alignment.
- Definitions that constrain pattern choices (e.g., "Customer owns CustomerId" forbids cross-context FKs).
- Form opinions: which patterns to follow, which to deviate from, and why.
Phase 2 — Surface Patterns
Present patterns you intend to follow as a structured block:
- Pattern: [what]
- Found in: [where, prevalence — e.g., "12/15 files in
internal/auth/"] - Intend to follow: yes / no / partially
- Reason: [why]
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.
- yesterday First seen · 275 lines · 45 tokens per session scan A a59486fde3b1
alignment is a skill published in the GitHub repository xobotyi/cc-foundry (20 stars, last pushed 2d ago), licensed MIT. It adds 45 tokens to every session and 2,877 once invoked, about $0.0002 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 2026-09-04.
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