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 commands/not-diamond/self-care/analyzegit clone --depth 1 https://github.com/Not-Diamond/self-careWrote 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/not-diamond/self-care/analyze)<a href="https://agentmods.dev/commands/not-diamond/self-care/analyze"><img src="https://agentmods.dev/badge/commands/not-diamond/self-care/analyze.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 | $0.00008 | $0.02173 |
| Opus 5 | $0.00004 | $0.01086 |
| Sonnet 5 | $0.00002 | $0.00435 |
| Haiku 4.5 | $0.00001 | $0.00217 |
Grade A, and why
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 4d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Trace
Validate and analyze the provided trace file for cases (grounding, missed-action, instruction-following, context-utilization, goal-drift, persona-adherence, reasoning-action-mismatch, step-repetition, tool-failure, premature-termination, contradictory-instructions, missing-context, ambiguous-instructions, guardrail-violation). Supports both OTEL (JSON) and Claude Code (JSONL) formats.
Arguments
<trace-file>: Path to the trace file (required)--hash <hash>: Pre-computed trace hash (optional). If provided, skipshasumcomputation and use this hash for memory lookup and output. This is a 16-character hex string.
Parse arguments: Extract the trace file path and optional --hash value from $ARGUMENTS. Example inputs:
"/path/to/trace.json"→ path="/path/to/trace.json", hash=null"/path/to/trace.json" --hash abc123def456789→ path="/path/to/trace.json", hash="abc123def456789"
Memory Behavior
Sift maintains persistent memory for each trace file to track cases across analysis runs:
- Memory storage:
.self-care/memory/<trace_hash>.jsonl - Trace hash: SHA256 of trace file content (first 16 characters), or provided via
--hash - Persistence: Events are tracked as "new" (first detection) or "recurring" (seen before)
- Resolution: Previously detected events that no longer appear are marked as "resolved"
Instructions
Stage 0: Parse Arguments
Extract the trace file path and optional flags from $ARGUMENTS:
-
If
$ARGUMENTScontains--hash, extract the hash value:- provided_hash: The value after
--hash(trimmed) - Remove
--hash <value>from the argument string
- provided_hash: The value after
-
Otherwise: provided_hash = null
-
If
$ARGUMENTScontains--skip-validation:- skip_validation = true
- Remove
--skip-validationfrom the argument string
-
Otherwise: skip_validation = false
-
The remaining string is trace_path (trimmed, with quotes removed)
-
If the prompt (not
$ARGUMENTS) contains an<analysis-config>block, extract its JSON content:- analysis_config_json: The JSON string inside the
<analysis-config>tags - This block appears after the command line in the prompt body (appended by the server)
- analysis_config_json: The JSON string inside the
-
Otherwise: analysis_config_json = null
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.
- 4d ago First seen · 224 lines · 8 tokens per session scan A 74b445cf206e
analyze is a command published in the GitHub repository Not-Diamond/self-care (28 stars, last pushed 4mo ago), licensed MIT. It adds 8 tokens to every session and 2,173 once invoked, about $0.0000 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.
Other commands, from other repositories
optimize
Show TokenJam's savings/optimize report — where quota is going and what's recoverable. Equivalent to running tj optimize.
status
Show TokenJam's current status for every tracked agent — token usage, cost today, and active alerts. Equivalent to running tj status.
uninstall
Remove TokenJam's Claude Code integration — unwires the statusline, hooks, and OTel env vars that /onboard set up. Equivalent to running tj uninstall --yes. Does not remove the plugin itself.
doctor
Run TokenJam's health check — config, ingest endpoint, and storage. Equivalent to running tj doctor.
onboard
Set up TokenJam for this Claude Code install — wires the zero-token statusline, the resume-brief SessionStart hook, and local OTel telemetry ingest via the existing tj onboard command. Runs 100% locally, no signup.
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.