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/sandeep-alluru/agentdelta/diffgit clone --depth 1 https://github.com/sandeep-alluru/agentdeltaWhat 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 | $0.00000 | $0.00293 |
| Opus 5 | $0.00000 | $0.00147 |
| Sonnet 5 | $0.00000 | $0.00059 |
| Haiku 4.5 | $0.00000 | $0.00029 |
Grade A, and why
diff 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 today.
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
Diff two agentdelta trace files and report any behavioral regression.
Usage: /project:diff <baseline.jsonl> <candidate.jsonl> [--format rich|json|markdown] [--exit-code]
Steps:
- Run:
agentdelta diff $ARGUMENTS - Parse the output:
- "REGRESSION DETECTED" → a ForkPoint was found; show the fork step, tool change, and similarity score
- "No regression" → traces are equivalent; show match percentage
- If a fork is detected, explain in plain English what changed:
- Tool change (e.g. get_weather → web_search): mention latency/reliability implications
- Reasoning divergence: mention that the LLM reasoning path changed even if the final answer is the same
- Step count difference: mention added/removed tool calls
- Suggest a remediation if asked: tighten the system prompt, pin the model version, or add a unit test fixture for this trace pair.
Context:
- Traces are JSONL files — one JSON object per line (trace_meta, node, edge records)
- Fork threshold default: 0.70 cosine similarity
- Match threshold default: 0.85 cosine similarity
- The embedding model is all-MiniLM-L6-v2, runs locally, no API key needed
has_regressionis True iff fork_point is not None
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.
- today First seen · 22 lines · 0 tokens per session scan A bc3b9e55834c
diff is a command published in the GitHub repository sandeep-alluru/agentdelta (0 stars, last pushed 14d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 293 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 2026-08-31.
Other commands, from other repositories
resolve
Use the GitWand CLI to automatically resolve trivial merge conflicts, then handle remaining complex hunks manually.
pre-commit
Run pre-commit checks identical to GitHub CI (ruff, mypy, tests).
using-pensyve
Show available Pensyve memory tools, skills, and commands.
on
Turn diffscope's automatic change briefing back on.
memory-status
Show Pensyve memory namespace statistics and health overview.
recall
Search Pensyve memory by semantic similarity and text matching.