Borrowing it
Nothing to install: this file belongs to rossumai/rossum-agents. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/rossumai/rossum-agents/master/.claude/commands/ds-analyze-chats.mdgit clone --depth 1 https://github.com/rossumai/rossum-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/commands/rossumai/rossum-agents/ds-analyze-chats)<a href="https://agentmods.dev/commands/rossumai/rossum-agents/ds-analyze-chats"><img src="https://agentmods.dev/badge/commands/rossumai/rossum-agents/ds-analyze-chats/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/commands/rossumai/rossum-agents/ds-analyze-chats"><img src="https://agentmods.dev/badge/commands/rossumai/rossum-agents/ds-analyze-chats.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 | $0.00000 | $0.01872 |
| Opus 5 | $0.00000 | $0.00936 |
| Sonnet 5 | $0.00000 | $0.00374 |
| Haiku 4.5 | $0.00000 | $0.00187 |
Grade A, and why
ds-analyze-chats 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Chat Data
Goal: Analyze rossum-agent chat data from a CSV export to identify improvement opportunities for rossum-agent and rossum-mcp.
Input
$ARGUMENTS = path to a CSV file containing PostgreSQL-exported chat rows.
If no argument provided, prompt the user for the file path.
Data Format
Each line is a PostgreSQL tuple: (db_id, chat_id, messages_jsonb, output_dir, metadata_jsonb, created_at, expires_at)
| Field | Format | Key contents |
|---|---|---|
messages |
JSONB array | Steps: task_step (user turns), memory_step (agent reasoning + tool calls) |
metadata_ |
JSONB object | persona, summary, mcp_mode, total_steps, total_tool_calls, total_input_tokens, total_output_tokens, config_commits |
Step types inside messages
| Type | Contains |
|---|---|
task_step |
task (user message — see note below), preload_info |
memory_step |
step_number, text, tool_calls[{name, arguments}], tool_results[{name, content, is_error}], thinking_blocks, input_tokens, output_tokens |
task field: Can be a str or a list of content blocks (e.g., [{"type": "text", "text": "..."}, {"type": "image", ...}]). Extract text by joining all text-type items. Always normalize to string before classification.
Analysis Pipeline
Write a single Python script via cat << 'PYEOF' > $TMPDIR/analyze_chats.py ... PYEOF (avoids Write tool guard issues), then run it. All phases in one script, output results to stdout.
Parsing Requirements
The export is PostgreSQL COPY format with JSONB fields. Parsing is non-trivial:
| Requirement | Implementation |
|---|---|
| Field size | csv.field_size_limit(sys.maxsize) — JSONB fields exceed default 131072 limit |
| CSV dialect | csv.reader(f) — fields are comma-separated, quoted with "" escaping |
| Backslash unescaping | Iteratively replace \\\\ → \\ until stable before json.loads() |
| Quote unescaping | Replace "" → " within quoted fields (handled by csv.reader) |
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.
- 11d ago First seen · 172 lines · 0 tokens per session scan A ccd290a505b2
ds-analyze-chats is a command published in the GitHub repository rossumai/rossum-agents (11 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,872 tokens. 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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