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 digital-stoic-org/agent-skills --skill pingit clone --depth 1 https://github.com/digital-stoic-org/agent-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/digital-stoic-org/agent-skills/pin)<a href="https://agentmods.dev/skills/digital-stoic-org/agent-skills/pin"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/pin/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/digital-stoic-org/agent-skills/pin"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/pin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 13 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00132 | $0.01413 |
| Opus 5.5 | $0.00053 | $0.00565 |
| Sonnet 5.5 | $0.00026 | $0.00283 |
| Haiku 4.5 | $0.00013 | $0.00141 |
Grade A, and why
pin 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pin — Session Decision Board
Persist decisions, questions, constraints, and corrections to a JSON file that survives context compaction. A companion hook injects the board into every tool call so the model never forgets.
Auto-Invoke Rules
After responding to any user message where a decision was made, a question was asked about a proposal, or a constraint was stated, IMMEDIATELY invoke /pin with the appropriate category. Do not ask permission — just pin it.
Examples of auto-invoke triggers:
- User: "yes go with bun" → respond normally, then
/pin ✅ use bun - User: "what about the latency impact?" → respond normally, then
/pin ❓ split services — latency impact? - User: "no skip auth for now" → respond normally, then
/pin ❌ auth layer — skip for MVP - User: "MVP only, max 3 files" → respond normally, then
/pin 📌 MVP only, max 3 files - User: "no I meant artisans not developers" → respond normally, then
/pin 🔧 target = artisans, not developers
Do NOT pin:
- Casual conversation, greetings
- Implementation details (code changes, file edits)
- Things already pinned (check board first)
Commands
| Command | Action |
|---|---|
/pin ✅ <text> |
Pin approved item |
/pin ❓ <text> |
Pin pending question |
/pin ❌ <text> |
Pin killed/rejected item |
/pin 📌 <text> |
Pin scope constraint |
/pin 🔧 <text> |
Pin correction |
/pin show or /pin |
Display current board |
/pin rm <n> |
Remove pin by number |
/pin clear |
Clear all pins |
/pin clear triage |
Clear ✅/❓ only, keep 📌/❌/🔧 |
State File
Path: $PRAXIS_DIR/.session-logs/<slug>/pins.json
Derive slug from CWD:
GIT_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
REL_PATH="${PWD#$GIT_ROOT/}"
SLUG=$(echo "$REL_PATH" | tr '/' '-')
PINS_DIR="$PRAXIS_DIR/.session-logs/$SLUG"
PINS_FILE="$PINS_DIR/pins.json"
Schema:
{
"items": [
{
"id": 1,
"type": "approved",
"emoji": "✅",
"content": "use bun everywhere",
"detail": "",
"ts": "2026-04-01T14:30:00Z"
}
],
"next_id": 2
}
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 · 146 lines · 132 tokens per session scan A 48b5294851a5
pin is a skill published in the GitHub repository digital-stoic-org/agent-skills (20 stars, last pushed 12d ago), licensed MIT. It adds 132 tokens to every session and 1,413 once invoked, about $0.0005 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 2026-09-04.
Other skills, from other repositories
mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.