checkpoint-and-recover

checkpoint-and-recover is a skill for Claude Code, Codex from yogsoth-ai/de-anthropocentric-research-engine. It costs 17 tokens per session (814 once invoked), scanned A, original, Apache-2.0.

A safety pattern that saves the current state before a risky operation, watches for problems, checks the result, and decides whether to keep it or roll back.

In plain words
What is it for?
Use it around tasks that modify files or produce important outputs and need anomaly detection, validation, partial-result handling, or recovery.
Why use it?
It reduces the damage from failed or incomplete operations and preserves an audit trail of what happened.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it around tasks that modify files or produce important outputs and need anomaly detection, validation, partial-result handling, or recovery.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yogsoth-ai/de-anthropocentric-research-engine/checkpoint-and-recover
Install

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.

Any agent
npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill checkpoint-and-recover
Clone the repo
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for checkpoint-and-recover

README.md
[![agentmods](https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/checkpoint-and-recover/github.svg)](https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/checkpoint-and-recover)
Your own site
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/checkpoint-and-recover"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/checkpoint-and-recover/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.

agentmods 80×15 button for checkpoint-and-recover

Your own site · 80×15
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/checkpoint-and-recover"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/checkpoint-and-recover.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 814 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00017 $0.00814
Opus 5 $0.00009 $0.00407
Sonnet 5 $0.00003 $0.00163
Haiku 4.5 $0.00002 $0.00081

Measured 8d ago against content hash c911ce4ed6c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

checkpoint-and-recover 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 8d 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.

skills/checkpoint-and-recover/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tactic: Checkpoint and Recover

Orchestration Pattern

FUNCTION checkpoint_and_recover(task, execute_fn):
    // Pre-execution checkpoint
    checkpoint = {
        timestamp: now(),
        task_id: task.id,
        state: capture_current_state(),
        files_modified: [],
        outputs_produced: []
    }
    save_checkpoint(checkpoint)
    
    TRY:
        // Execute with monitoring
        monitor = SPAWN execution-monitoring(task)
        result = execute_fn(task)
        
        // Post-execution validation
        IF monitor.anomalies_detected:
            RAISE AnomalyError(monitor.anomalies)
        END
        
        // Validate result integrity
        validated = SPAWN result-collection(result, task.success_criterion)
        
        IF validated.complete AND validated.consistent:
            // Success — archive checkpoint (keep for audit trail)
            archive_checkpoint(checkpoint)
            RETURN {status: DONE, result: validated}
        ELSE:
            // Partial success — decide whether to keep or rollback
            IF validated.partial_value > threshold:
                archive_checkpoint(checkpoint)
                RETURN {status: PARTIAL, result: validated, missing: validated.gaps}
            ELSE:
                restore_state(checkpoint)
                RETURN {status: ROLLED_BACK, reason: validated.failure_reason}
            END
        END
        
    CATCH error:
        // Failure — diagnose and recover
        diagnosis = diagnose_failure(error, checkpoint, task)
        
        SWITCH diagnosis.severity:
            CASE TRANSIENT:
                // Retry without rollback (e.g., network timeout)
                RETURN {status: RETRY, reason: diagnosis}
                
            CASE CORRUPTING:
                // Rollback to checkpoint
                restore_state(checkpoint)
                RETURN {status: ROLLED_BACK, reason: diagnosis}
                
            CASE FATAL:
                // Rollback and escalate
                restore_state(checkpoint)
                RETURN {status: FATAL, reason: diagnosis, escalate: true}
        END
    END
END

Read the full file on GitHub · 124 lines

Changes

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.

  1. 8d ago First seen · 124 lines · 17 tokens per session scan A c911ce4ed6c3

Subscribe to this mod's changes

checkpoint-and-recover is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (456 stars, last pushed 2d ago), licensed Apache-2.0. It adds 17 tokens to every session and 814 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 2026-09-03.

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