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 skills add parcadei/Continuous-Claude-v3 --skill braintrust-analyzegit 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/skills/parcadei/continuous-claude-v3/braintrust-analyze)<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/braintrust-analyze"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/braintrust-analyze/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/parcadei/continuous-claude-v3/braintrust-analyze"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/braintrust-analyze.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 105 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Rogue Agent · line 15 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00012 | $0.00667 |
| Opus 5 | $0.00006 | $0.00333 |
| Sonnet 5 | $0.00002 | $0.00133 |
| Haiku 4.5 | $0.00001 | $0.00067 |
Grade A, and why
braintrust-analyze 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- braintrust-analyze — 100% identical, 212 lines differ
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Braintrust Analysis
Analyze your Claude Code sessions for patterns, issues, and insights using Braintrust tracing data.
When to Use
- After completing a complex task (retrospective)
- When debugging why something failed
- Weekly review of productivity patterns
- Finding opportunities to create new skills
- Understanding token usage trends
Commands
Run from the project directory:
# Analyze last session - summary with tool/agent/skill breakdown
uv run python -m runtime.harness scripts/braintrust_analyze.py --last-session
# List recent sessions
uv run python -m runtime.harness scripts/braintrust_analyze.py --sessions 5
# Agent usage statistics (last 7 days)
uv run python -m runtime.harness scripts/braintrust_analyze.py --agent-stats
# Skill usage statistics (last 7 days)
uv run python -m runtime.harness scripts/braintrust_analyze.py --skill-stats
# Detect loops - find repeated tool patterns (>5 same tool calls)
uv run python -m runtime.harness scripts/braintrust_analyze.py --detect-loops
# Replay specific session - show full sequence of actions
uv run python -m runtime.harness scripts/braintrust_analyze.py --replay <session-id>
# Weekly summary - daily activity breakdown
uv run python -m runtime.harness scripts/braintrust_analyze.py --weekly-summary
# Token trends - usage over time
uv run python -m runtime.harness scripts/braintrust_analyze.py --token-trends
Options
--project NAME- Braintrust project name (default: agentica)
What You'll Learn
Session Analysis
- Tool usage breakdown
- Agent spawns (plan-agent, debug-agent, etc.)
- Skill activations (/commit, /research, etc.)
- Token consumption estimates
Loop Detection
Find sessions where the same tool was called repeatedly, which may indicate:
- Stuck in a search loop
- Inefficient approach
- Opportunity for better tooling
Usage Patterns
- Which agents you use most
- Which skills get activated
- Daily/weekly activity trends
Examples
Quick Retrospective
# What happened in my last session?
uv run python -m runtime.harness scripts/braintrust_analyze.py --last-session
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 107 lines · 12 tokens per session scan A f94c9a5e4bc6
braintrust-analyze is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,937 stars, last pushed 7mo ago), licensed MIT. It adds 12 tokens to every session and 667 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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