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/pantheon-org/tekhne/save-contextnpx skills add pantheon-org/tekhne --skill save-contextgit clone --depth 1 https://github.com/pantheon-org/tekhneWrote 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/pantheon-org/tekhne/save-context)<a href="https://agentmods.dev/skills/pantheon-org/tekhne/save-context"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/save-context.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 | $0.00048 | $0.01609 |
| Opus 5 | $0.00024 | $0.00805 |
| Sonnet 5 | $0.00010 | $0.00322 |
| Haiku 4.5 | $0.00005 | $0.00161 |
Grade A, and why
save-context 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 4d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Save Context
Save current session state to .context/session/CONTEXT-{stream}-llm.md with LLM-optimized format.
Target: 1200-1500 tokens MAX | Speed: 3-5 seconds
AskUserQuestion Guard
CRITICAL: After EVERY AskUserQuestion call, check if answers are empty/blank. Known Claude Code bug: outside Plan Mode, AskUserQuestion silently returns empty answers without showing UI.
If answers are empty: DO NOT proceed with assumptions. Instead:
- Output: "Questions didn't display (known Claude Code bug outside Plan Mode)."
- Present the options as a numbered text list and ask user to reply with their choice number.
- WAIT for user reply before continuing.
Performance Rules
- Use
rtkfor ALL shell commands - Parallel tool calls — ALL independent calls in one message
- Minimize round-trips — gather all data phase 1, reason phase 2, write phase 3
Workflow
Phase 1: Gather Data (parallel)
Bash: rtk ls .context/session/ + rtk ls -t .context/session/CONTEXT-*llm.md
Stream resolution: First word of $ARGUMENTS = stream name (^[a-zA-Z0-9_-]{1,50}$), rest = description. Empty → reuse prior /load-context stream or AskUserQuestion.
Phase 2: Analyze & Synthesize (single pass)
From conversation (last 15-20 messages):
- Next — infer 3 tasks from conversation (IMPORTANT: use heading "Next" — Claude Code compaction grep-matches
next/todo/pending/remainingkeywords for survival priority) - Session — progression, decisions, thinking, unexpected (780 tokens max)
- Hot Files — max 10 discussed/edited
- Focus & Goal — 1-2 sentence focus + goal
Phase 3: Write & Report
Write CONTEXT file using template, then upsert .context/session/INDEX.md via scripts/upsert-index.sh.
Stream naming: "default" → .context/session/CONTEXT-llm.md, "{name}" → .context/session/CONTEXT-{name}-llm.md
Phase 3b: Auto-archive to .context/session/done/
If status is done or parked → move file to .context/session/done/ subfolder:
Bash: mkdir -p .context/session/done && mv .context/session/CONTEXT-{stream}-llm.md .context/session/done/
Report: "Archived to .context/session/done/ (status: {status})"
What ships with it
13 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.
- .audits/2026-04-11/analysis.md 1.2 KB
- .audits/2026-04-11/audit.json 485 B
- .audits/2026-04-11/remediation-plan.md 3.7 KB
- .audits/latest 10 B
- .tessl-plugin/plugin.json 236 B
- evals/instructions.json 1.5 KB
- evals/scenario-01.md 1.6 KB
- evals/scenario-02.md 1.6 KB
- evals/scenario-03.md 1.9 KB
- evals/scenario-04.md 1.6 KB
- evals/scenario-05.md 1.7 KB
- reference.md 3.0 KB
- scripts/upsert-index.sh 2.2 KB runs code
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.
- 4d ago First seen · 135 lines · 48 tokens per session scan A 4f2a677d4b17
save-context is a skill published in the GitHub repository pantheon-org/tekhne (10 stars, last pushed 3d ago), licensed MIT. It adds 48 tokens to every session and 1,609 once invoked, about $0.0002 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 2026-08-31.
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
使用于 Comet 需要根据有界语义评审包判断是否值得保存个人记忆、候选、更新、遗忘或跳过时。.
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.
immune
Hybrid adaptive memory: Cheatsheet (positive patterns pre-generation) and Immune (negative patterns post-generation) with Hot/Cold tiered auto-learning. Triggers on: "scan for errors", "immune scan", "check output quality", "antibody scan". NOT for PR review (use pr-review) or repo audits (use repo-sentinel).
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.
memory-md-management
Provides comprehensive memory file management capabilities including auditing, quality assessment, and targeted improvements for files such as CLAUDE.md. Use when user asks to check, audit, update, improve, fix, maintain, or validate project memory files. Also triggers for "project memory optimization", "CLAUDE.md…