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/buiphucminhtam/forgewright/instinct-systemnpx skills add buiphucminhtam/forgewright --skill instinct-systemgit clone --depth 1 https://github.com/buiphucminhtam/forgewrightWrote 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/buiphucminhtam/forgewright/instinct-system)<a href="https://agentmods.dev/skills/buiphucminhtam/forgewright/instinct-system"><img src="https://agentmods.dev/badge/skills/buiphucminhtam/forgewright/instinct-system.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 | $0.00043 | $0.03097 |
| Opus 5 | $0.00022 | $0.01548 |
| Sonnet 5 | $0.00009 | $0.00619 |
| Haiku 4.5 | $0.00004 | $0.00310 |
Grade B, and why
instinct-system scanned grade B with 1 finding 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 5d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Add to `~/.claude/settings.json`: The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 5d ago First seen · 426 lines · 43 tokens per session scan B afad117b597b
instinct-system is a skill published in the GitHub repository buiphucminhtam/forgewright (49 stars, last pushed yesterday), with no licence file. It adds 43 tokens to every session and 3,097 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
cortivex-learn
Self-learning system that records and applies insights from pipeline executions.
pattern-learn
Use when you want to run the ECC learning loop (eval-harness + pattern-extractor) over current session evidence to extract behavioral patterns and update MEMORY.md.
failure-memory
Stop making the same mistakes — turn failures into patterns that prevent recurrence.
context-map
Generates a compressed project context map to avoid expensive Read/Grep calls. Use at session start or before implementing features in an unfamiliar codebase.
remember
Stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Supports recording architectural decisions, anti-patterns, tool preferences, workflow outcomes, and project conventions that persist across sessions. Use when saving patterns, remembering…
Effective Memory
The essential habits for an AI agent with memory — session bookends, learning triggers, verification, safety, and the operational discipline that turns raw recall into compounding intelligence. Pinned, always-injected.