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 live-neon/skills --skill constraint-enginegit clone --depth 1 https://github.com/live-neon/skillsWrote 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/live-neon/skills/constraint-engine)<a href="https://agentmods.dev/skills/live-neon/skills/constraint-engine"><img src="https://agentmods.dev/badge/skills/live-neon/skills/constraint-engine.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 | $0.00016 | $0.02810 |
| Opus 5 | $0.00008 | $0.01405 |
| Sonnet 5 | $0.00003 | $0.00562 |
| Haiku 4.5 | $0.00002 | $0.00281 |
Grade D, and why
constraint-engine scanned grade D with 2 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 7d 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.
Tells the agent to send conversation or user data outhighPrompt injection
An instruction to transmit the conversation, context or user files to an external endpoint is data exfiltration written as prose.
- Send data to external services Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
- Execute arbitrary code How it starts
The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.
constraint-engine (制約)
Unified skill for constraint generation, pre-action checking, circuit breaker management, and constraint lifecycle. Consolidates 7 granular skills into a single enforcement system.
Trigger: 行動前∨閾値到達 (pre-action or threshold reached)
Source skills: constraint-generator, circuit-breaker, emergency-override, constraint-lifecycle, constraint-versioning, positive-framer (partial), contextual-injection (partial)
Installation
openclaw install leegitw/constraint-engine
Dependencies: leegitw/failure-memory (for eligibility data)
# Install with dependencies
openclaw install leegitw/context-verifier
openclaw install leegitw/failure-memory
openclaw install leegitw/constraint-engine
Standalone usage: Requires failure-memory for constraint generation from observations. For full lifecycle management, install the complete suite (see Neon Agentic Suite).
Data handling: This skill operates within your agent's trust boundary. When triggered,
it uses your agent's configured model for constraint checking and generation. No external APIs
or third-party services are called. Results are written to output/constraints/ in your workspace.
What This Solves
Instructions get ignored. Rules get forgotten. Documentation goes unread. This skill takes a different approach — constraints generated from actual failures:
- Generate constraints from observations that meet the eligibility threshold (
R≥3 ∧ C≥2) - Enforce constraints at runtime with a circuit breaker (CLOSED → OPEN → HALF-OPEN)
- Manage lifecycle from proposal through adoption to retirement
The insight: A constraint born from "this actually broke" carries more weight than "this might break." Consequences teach better than instructions.
Usage
/ce <sub-command> [arguments]
Sub-Commands
| Command | CJK | Logic | Trigger |
|---|---|---|---|
/ce check |
検査 | action→constraints[]→pass∨block | Next Steps (auto) |
/ce generate |
生成 | eligible(obs)→constraint | Next Steps (auto) |
/ce status |
状態 | active[], circuit∈{CLOSED,OPEN,HALF} | Explicit |
/ce override |
上書 | constraint→bypass(temp), audit.log++ | Explicit |
/ce lifecycle |
周期 | state∈{draft→active→retiring→retired} | Explicit |
/ce version |
版本 | constraint→v++, history.preserve | Explicit |
/ce threshold |
閾値 | user∨context→custom_threshold | Explicit |
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.
- 7d ago First seen · 375 lines · 16 tokens per session scan D 9f576a26f446
constraint-engine is a skill published in the GitHub repository live-neon/skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 16 tokens to every session and 2,810 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it D with 2 findings (tells the agent to send conversation or user data out, unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
mpm-circuit-breaker-enforcement
Complete circuit breaker enforcement patterns with examples and remediation.
rules-eval
Evaluate Claude Code rules in .claude/rules/. Use for frontmatter, globs, and quality audits.
theme-sect-discipline
A themed code-quality and review guide built around inspection, finding problems, correction, and acceptance. It includes checks for reading failure details, inspecting source context, validating assumptions, and reproducing issues in isolation.
phase-enforcement
Evidence-based phase completion enforcement for /dev:feature. Use when orchestrating 8-phase feature development to ensure artifacts exist before phase completion, validation criteria are addressed, outer loops are enforced, and show-your-work requirements are met.
writing-rules
Creates behavioral rules in markdown to block dangerous commands or restrict AI behavior. Use when adding safety guardrails or preventing specific commands.
agent-guardrails
Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.