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 commands/ozgurkarahan/ai-agent-memory/statusgit clone --depth 1 https://github.com/ozgurkarahan/ai-agent-memoryWrote 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/commands/ozgurkarahan/ai-agent-memory/status)<a href="https://agentmods.dev/commands/ozgurkarahan/ai-agent-memory/status"><img src="https://agentmods.dev/badge/commands/ozgurkarahan/ai-agent-memory/status.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 | $0.00000 | $0.00685 |
| Opus 5 | $0.00000 | $0.00342 |
| Sonnet 5 | $0.00000 | $0.00137 |
| Haiku 4.5 | $0.00000 | $0.00068 |
Grade A, and why
status 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 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.
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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/status — Project Briefing
When the user types /status, produce a 30-second situational-awareness briefing on this project so they can get up to speed instantly.
Gather information from all the sources below in parallel, then produce a single structured briefing.
1. Codebase analysis
- Tech stack: languages, frameworks, key dependencies (check
package.json,requirements.txt,pyproject.toml,*.csproj,Cargo.toml,go.mod,pom.xml, etc.) - Folder structure: high-level tree (max 2 levels deep)
- Entry points / key files: config files, main modules
- Architecture patterns: monolith / microservices, API style (REST / GraphQL / gRPC), state management
- Size: approximate source files + LOC
2. Project history
- Read
AGENT.mdfor the project overview and objectives git log --oneline --since="2 weeks ago"— recent activitygit log -5 --format="%h %s (%ar)"— last 5 commits with relative datesgit log --oneline --all | tail -5— earliest commits (for context)
3. Last modifications
git diff --stat HEAD~3(if enough commits exist) — what files changed recentlygit status— uncommitted work in progressgit branch -a— open branchesgit stash list— stashed work
4. Deployment status
Check for deployment indicators:
- Azure (azd):
azure.yaml,.azure/,infra/*.bicep - GitHub Actions:
.github/workflows/ - Docker:
Dockerfile,docker-compose.yml - Other CI/CD:
.gitlab-ci.yml,Jenkinsfile,.circleci/,bitbucket-pipelines.yml - Git tags:
git tag --sort=-creatordate | head -5
If no deployment config is found, say "No deployment configuration detected".
5. Current state
- Current branch and its relation to main / master
- Uncommitted changes / stashed work
- Open
TODO,FIXME,HACKcount in source files
Output format
## 🔍 Project Status: {project name}
### Tech Stack
{languages, frameworks, key deps — one line each}
### Architecture
{folder overview + patterns — brief}
### History
- **Created:** {first commit date}
- **Total commits:** {count}
- **Recent activity:** {last 2 weeks summary}
### Last 5 Changes
{table: hash | message | when}
### Deployment
{deployment config + last deploy info if known}
### Current State
- **Branch:** {current branch}
- **Uncommitted work:** {yes/no + summary}
- **Open TODOs:** {count}
### Key Takeaways
{2-3 bullets — what's the most important thing to know right now}
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 · 79 lines · 0 tokens per session scan A 3e5d1084537f
status is a command published in the GitHub repository ozgurkarahan/ai-agent-memory (8 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 685 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.