Borrowing it
Nothing to install: this file belongs to AmanKtyr/Tailor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AmanKtyr/Tailor/main/.agents/skills/project-memory/SKILL.mdgit clone --depth 1 https://github.com/AmanKtyr/TailorWrote 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/amanktyr/tailor/project-memory)<a href="https://agentmods.dev/skills/amanktyr/tailor/project-memory"><img src="https://agentmods.dev/badge/skills/amanktyr/tailor/project-memory/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/amanktyr/tailor/project-memory"><img src="https://agentmods.dev/badge/skills/amanktyr/tailor/project-memory.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00032 | $0.00572 |
| Opus 5.5 | $0.00013 | $0.00229 |
| Sonnet 5.5 | $0.00006 | $0.00114 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
project-memory 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Memory Skill
Activate this skill when reading, creating, updating, or repairing .ai/ memory files, resolving documentation drift, or managing agent context windows.
Operational Principle: Project memory is an indexed cache of project facts. Source code is the ultimate ground truth.
1. Project Memory Hierarchy & Source of Truth
When conflicting information is detected between files:
- Source of Truth 1 (Highest): Verifiable source code, database schemas (
schema.prisma,models.py,migrations/), and package manifests (package.json,Cargo.toml,go.mod). - Source of Truth 2: Project Memory Files (
.ai/STACK.md,.ai/API.md,.ai/DATABASE.md). - Source of Truth 3 (Lowest): Outdated inline comments, legacy markdown notes, or unverified chat instructions.
If memory conflicts with source code: Trust the source code, flag the drift, and immediately update the memory document.
2. Progressive Disclosure Rules (Token Optimization)
To minimize context token consumption and maintain maximum LLM reasoning capacity:
- Entry Point: Always read
.ai/CONSTITUTION.mdand.ai/INDEX.mdfirst. - Domain Documents (Read strictly on demand):
- Architecture decisions:
.ai/ARCHITECTURE.md,.ai/DECISIONS.md - UI components and design tokens:
.ai/UI.md,.ai/CONVENTIONS.md - Endpoints, contracts, and payloads:
.ai/API.md - Schemas, migrations, and ORMs:
.ai/DATABASE.md - Installed packages and governance:
.ai/DEPENDENCIES.md - Security policies and secret management:
.ai/SECURITY.md - Verification runners and commands:
.ai/TESTING.md
- Architecture decisions:
3. Drift Detection & Live Repair Workflow
When finishing any non-trivial coding task or executing /update-project-memory:
- Check if dependencies were added, removed, or upgraded. If so, synchronize
.ai/DEPENDENCIES.md. - Check if new database models or migrations were introduced. If so, synchronize
.ai/DATABASE.md. - Check if new API endpoints or route contracts were created. If so, synchronize
.ai/API.md. - Check if new architectural decisions were adopted. If so, record an ADR in
.ai/DECISIONS.md. - Verify that
.ai/INDEX.mdaccurately references all active domain memory files.
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 · 48 lines · 32 tokens per session scan A b94173bb4ede
project-memory is a skill published in the GitHub repository AmanKtyr/Tailor (6 stars, last pushed 11d ago), licensed MIT. It adds 32 tokens to every session and 572 once invoked, about $0.0001 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 2026-08-31.
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