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 Daisybastioned440/lite-research-agents --skill memory-checkpointgit clone --depth 1 https://github.com/Daisybastioned440/lite-research-agentsWrote 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/daisybastioned440/lite-research-agents/memory-checkpoint)<a href="https://agentmods.dev/skills/daisybastioned440/lite-research-agents/memory-checkpoint"><img src="https://agentmods.dev/badge/skills/daisybastioned440/lite-research-agents/memory-checkpoint/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/daisybastioned440/lite-research-agents/memory-checkpoint"><img src="https://agentmods.dev/badge/skills/daisybastioned440/lite-research-agents/memory-checkpoint.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00016 | $0.00565 |
| Opus 5.5 | $0.00006 | $0.00226 |
| Sonnet 5.5 | $0.00003 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
memory-checkpoint 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.
This is a copy
100% identical to memory-checkpoint — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Checkpoint
Defines how to save a checkpoint and how to load one into SI. When to checkpoint is determined by the calling context — the project, the war room, or the agent's own judgment.
How to Save
Create a timestamped folder under memory/checkpoints/. Inside it, write one file per agent indexed by agent number.
memory/checkpoints/YYYYMMDD_HHMMSS/
├── agent-0.md
├── agent-1.md
└── ...
Each agent-N.md captures that agent's state. No length constraints — summarise what is needed to resume. A good checkpoint captures what would be hard to reconstruct, not a verbatim log.
# Agent <N> — <timestamp>
**Role**: <role>
**Trigger**: <what caused this checkpoint>
**Completed**: <what was just finished>
**Next**: <exact next action>
## State
<key facts, file paths, env state, decisions made, blockers — whatever is needed to resume>
After writing all agent files, update memory/SUMMARY.md — rewrite it to point to the latest checkpoint.
# Summary
- **Last checkpoint**: `memory/checkpoints/<timestamp>/`
- **Status**: <not_started | in_progress | blocked | complete>
## State
<key facts — file paths, important values, decisions that affect what comes next>
## Resume From
<one clear instruction: what to do next, any preconditions>
How to Load
On resume, inject into SI in this order:
- Read
memory/SUMMARY.md— always first. Get current status and the latest checkpoint path. - Read the relevant
agent-N.mdfrom the latest checkpoint folder — inject the file for your agent index. - Load other agents' files only if needed — e.g. to understand what another agent did.
- Load older checkpoints only if needed — e.g. to understand a past decision.
Layout
memory/
├── SUMMARY.md
└── checkpoints/
├── 20260328_090000/
│ └── agent-0.md
├── 20260328_142301/
│ ├── agent-0.md
│ └── agent-1.md
└── 20260328_154732/
├── agent-0.md
└── agent-1.md
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 · 81 lines · 16 tokens per session scan A 491f7100fe3f
memory-checkpoint is a skill published in the GitHub repository Daisybastioned440/lite-research-agents (3 stars, last pushed 9d ago), licensed MIT. It adds 16 tokens to every session and 565 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to memory-checkpoint, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
dpf-elicit-tacit-knowledge
Use when durable DPF knowledge lives only in a human's head — a decision rationale, the why behind a choice, a profession technique, domain context a build depends on.
do-it-context
Use when project terms, relationships, or invariants drift between user language, docs, and implementation, or when stable project knowledge keeps being rediscovered or the user asks to document it.
dpf-route-learning-to-commons
Use in the DPF codebase at a task or session boundary when a finding has been confirmed and is durable.
note
Save learnings and discoveries to NOTES.md for persistence across sessions.
context-compression
Use Tokenless for large files and noisy tool outputs before they enter context. Must be used when commands, Read output, diffs, logs, or search results are large.
wiki
Use this skill for explicit wiki setup or maintenance, including creation without an existing wiki, and for post-review ingest evaluation and conditional ingestion when the task belongs to an identified project with wiki/ at its root. For read-only consultation alone, load wiki-query instead.