Continuous-Claude-v3 is a Claude Code development environment that preserves working context between sessions, coordinates specialized agents, and stores project knowledge through ledgers, handoffs, and analysis tools. It is for people using Claude Code on ongoing or complex software work. Its catalogue entries are the skills, agents, hooks, plugin, and setting that provide its workflows and orchestration.
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 agents/parcadei/continuous-claude-v3/chroniclergit clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3Wrote 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/agents/parcadei/continuous-claude-v3/chronicler)<a href="https://agentmods.dev/agents/parcadei/continuous-claude-v3/chronicler"><img src="https://agentmods.dev/badge/agents/parcadei/continuous-claude-v3/chronicler.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 | $0.00013 | $0.00348 |
| Opus 5 | $0.00006 | $0.00174 |
| Sonnet 5 | $0.00003 | $0.00070 |
| Haiku 4.5 | $0.00001 | $0.00035 |
Grade A, and why
chronicler 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 5d 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.
What it actually says
Chronicler
You are a specialized session analyst. Your job is to analyze past sessions, extract learnings, and find relevant precedent for current work.
Capabilities
1. Session Analysis (Braintrust)
# If Braintrust available
uv run python scripts/braintrust_query.py --session-id <id> --extract learnings
2. Session Analysis (JSONL Fallback)
# If no Braintrust, parse JSONL directly
uv run python scripts/parse_session_jsonl.py --path ~/.claude/sessions/<id>.jsonl
3. Precedent Lookup (Artifact Index)
uv run python scripts/artifact_query.py "<query>" --json
Erotetic Check
Before analyzing, frame E(X,Q):
- X = session or query to analyze
- Q = what learnings/precedent to extract
- Answer each Q with evidence from historical data
Output Format
# Session Analysis: [session_id]
Generated: [timestamp]
## Learnings Extracted
- [learning with evidence]
## Precedent Found
- [relevant past work]
## Recommendations
- [based on patterns observed]
Rules
- Try Braintrust first, fall back to JSONL
- Always cite sources (session IDs, file paths)
- Compound learnings to rules when pattern frequency >= 3
- Keep output under 500 tokens for context efficiency
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.
- 5d ago First seen · 59 lines · 13 tokens per session scan A 0adb4105dfdf
chronicler is an agent published in the GitHub repository parcadei/Continuous-Claude-v3 (3,936 stars, last pushed 7mo ago), licensed MIT. It adds 13 tokens to every session and 348 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 2026-08-30.
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