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 jellydn/my-ai-tools --skill qmd-knowledgegit clone --depth 1 https://github.com/jellydn/my-ai-toolsWrote 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/jellydn/my-ai-tools/qmd-knowledge)<a href="https://agentmods.dev/skills/jellydn/my-ai-tools/qmd-knowledge"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/qmd-knowledge/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/jellydn/my-ai-tools/qmd-knowledge"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/qmd-knowledge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 82 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 246 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Rogue Agent · line 136 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00020 | $0.02030 |
| Opus 5 | $0.00010 | $0.01015 |
| Sonnet 5 | $0.00004 | $0.00406 |
| Haiku 4.5 | $0.00002 | $0.00203 |
Grade A, and why
qmd-knowledge 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 10d 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 — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QMD Knowledge
What I do
- Record and retrieve project learnings and insights
- Capture issue-specific notes and resolutions
- Build a growing, AI-searchable knowledge base
- Provide context about project architecture and decisions
When to use me
Use this skill when you need to:
- Record learnings: Capture new insights, patterns, or best practices discovered during development
- Track issues: Add notes to ongoing or resolved issues
- Query knowledge: Search for previous decisions, learnings, or solutions
- Maintain context: Build institutional memory for the project
How it works
This skill provides a unified knowledge management system. You install the skill once, and it manages knowledge across all your projects using qmd collections:
# The qmd-knowledge skill (installed to your AI tool's skills directory)
# Location varies by tool: $HOME/.config/opencode/skills/, $HOME/.claude/skills/, or $HOME/.config/amp/skills/
├── SKILL.md # This file - the skill definition
├── scripts/ # Executable scripts
│ └── record.sh # Record learnings/issues/notes
└── references/ # Example structure and READMEs
# Project knowledge storage (managed by the skill)
~/.ai-knowledges/
├── <project-name>/ # Collection for your project
│ ├── learnings/
│ └── issues/
└── another-project/ # Collection for another project
├── learnings/
└── issues/
The qmd MCP server provides AI-powered search across all stored knowledge, allowing your AI assistant to autonomously query and update the knowledge base.
Available scripts
Recording knowledge
Important: Before recording knowledge, ensure qmd is installed and your project collection is set up. Run a preflight check:
# Verify qmd is installed
command -v qmd || echo "Install qmd: bun install -g @tobilu/qmd"
# Verify your project collection exists (replace my-project with your actual project name)
qmd collection list | grep my-project
What ships with it
3 files 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.
- 10d ago First seen · 256 lines · 20 tokens per session scan A 742d64089dc3
qmd-knowledge is a skill published in the GitHub repository jellydn/my-ai-tools (120 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 2,030 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
comet-memory
A review step for deciding whether information should become durable personal memory. It can keep, update, forget, or skip memory candidates based on bounded evidence.
recall-memory
Recall relevant long-term memories on demand. Given a topic or question, judges relevance from pre-loaded metadata, loads only relevant files, and returns a concise summary to the main agent.
agent-expert-creation
Create specialized agent experts with pre-loaded domain knowledge using the Act-Learn-Reuse pattern. Use when building domain-specific agents that maintain mental models via expertise files and self-improve prompts.
relevance-coarse-filter
Cheap, high-recall first-pass filter that removes obvious junk from a detector candidate pool before expensive story-origin research and PR judgment. Decides keep, monitoronly, or reject — never ranks, writes angles, verifies dates, or decides whether to pitch.
self-improve
Extract lessons from the current session, or sweep the project's past sessions when asked, and route them to the appropriate knowledge layer (project AGENTS.md, auto memory, existing skills, or new skills). Use when the user asks to "self-improve", "distill this session", "distill past sessions", "sweep past…