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 KimYx0207/Meta_Kim --skill save-progressgit clone --depth 1 https://github.com/KimYx0207/Meta_KimWrote 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/kimyx0207/meta_kim/save-progress)<a href="https://agentmods.dev/skills/kimyx0207/meta_kim/save-progress"><img src="https://agentmods.dev/badge/skills/kimyx0207/meta_kim/save-progress/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/kimyx0207/meta_kim/save-progress"><img src="https://agentmods.dev/badge/skills/kimyx0207/meta_kim/save-progress.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00065 | $0.01183 |
| Opus 5.5 | $0.00026 | $0.00473 |
| Sonnet 5.5 | $0.00013 | $0.00237 |
| Haiku 4.5 | $0.00006 | $0.00118 |
Grade A, and why
save-progress scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Save Progress
Saves current task progress to .claude/project-task-state.json in the project directory so the next session can automatically load it and resume where you left off.
What to Save
Before invoking this command, you should know:
- Current task: What are you working on RIGHT NOW?
- Completed tasks: What has been finished in this session? (Be specific, not "various things")
- Remaining tasks: What still needs to be done?
How to Invoke
# Detect the Python hook path — it lives in ~/.claude/hooks/
python "$HOME/.claude/hooks/mcp_memory_global.py" \
--mode save \
--task "Describe current task in one sentence" \
--done "Task 1 completed" "Task 2 completed" \
--remaining "Next task to do" "Another remaining task"
Or use the Claude Code hooks path from the user profile if HOME is not set:
python "%USERPROFILE%/.claude/hooks/mcp_memory_global.py" ^
--mode save ^
--task "..." ^
--done "..." ^
--remaining "..."
When to Save
Trigger this when:
- User explicitly asks to save progress
- Session is being interrupted (detected via hook or user signal)
- A major milestone is completed
- Before switching to a different project
- End of a work session
What NOT to Save
- Generic "worked on project" — be specific: "completed dependency license audit for 4 READMEs"
- Session noise — only save meaningful task state
- Duplicate entries — if nothing meaningful changed, don't overwrite
Output
The command returns JSON with:
saved: booleanfile: path to the state filetotal_sessions: number of sessions recordedtotal_completed: total completed tasks across all sessionslast_session_completed: how many tasks completed this sessionlast_session_remaining: remaining tasks as of this save
Show the user a brief summary after saving.
Example
User says: "save progress"
python "$HOME/.claude/hooks/mcp_memory_global.py" \
--mode save \
--task "Audit Meta_Kim dependencies and update 4 READMEs" \
--done "Audited npm dependency licenses" "Audited GitHub skill repositories" "Wrote English README dependency section" \
--remaining "Update localized READMEs" "Push to GitHub" \
--note "Found CLI-Anything is Apache 2.0, not MIT"
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 · 133 lines · 65 tokens per session scan A a42cd2179360
save-progress is a skill published in the GitHub repository KimYx0207/Meta_Kim (284 stars, last pushed today), licensed Apache-2.0. It adds 65 tokens to every session and 1,183 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
session-management
Context preservation, tiered summarization, resumability.
context-shunt
Offload large / multi-file reads to a cheap worker model so raw files never enter Claude's context (token savings).
identity-snapshot
Generate a living profile of the user's working patterns, decision tendencies and quality preferences from their Dex data. Use when the user says 'what are my patterns', 'how do I work', or during week-review. Also use proactively when the model (older than 7 days) is stale. Not for planning a week; use week-plan.
memorix-memory
Use when prior workspace context, past decisions, solved bugs, handoff state, or durable project knowledge would help a coding task.
memorix
Use when Claude Code needs Memorix shared memory, reasoning, Git Memory, mini-skills, session handoff, orchestration coordination, or integration troubleshooting.
memorix-mini-skills
Use when durable project knowledge, gotchas, workflows, or repeated fixes should become reusable agent guidance instead of ordinary memory.