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AC chronicle

Preserve operational history and intent across agent sessions. Use when resuming work, recording a decision, preparing a destructive or bulk operation, verifying a deployment, correcting a claim, reconstructing a captured file version, or handing off unfinished work.

ClawHub Agent Skills author: Antreas Antoniou v1.0.0 MIT-0 24 files · 1 script body ≈ 754 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Preserve operational history and intent across agent sessions.

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructureAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
98
Quality 40%
86
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-labelled-token src/chronicle/capture.py:1284
      Labelled token / key literal (vendor format unknown — verify it is not a live credential) (placeholder value)
      red = redact_text("export API_KEY=sk-l…bcd")
      placeholder
    • low Secrets in code secret-password-literal src/chronicle/capture.py:1284
      Hard-coded password / key literal (may be an example) (placeholder value)
      red = redact_text("export API_KEY=sk-l…bcd")
      placeholder

    Files scanned: 20. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 52/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 5 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 4 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 754 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 267: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 4 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    Chronicle appears to be a legitimate history tool, but it uses persistent broad capture of commands, prompts, files, transcripts, remotes, and model processing with enough scoping and redaction risk to require Review.
    LLM: suspicious (high) · 5 Sept 2026