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 skills/awrshift/agent-memory-kit/session-reviewnpx skills add awrshift/agent-memory-kit --skill session-reviewgit clone --depth 1 https://github.com/awrshift/agent-memory-kitWhat 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 | $0.00149 | $0.01242 |
| Opus 5 | $0.00075 | $0.00621 |
| Sonnet 5 | $0.00030 | $0.00248 |
| Haiku 4.5 | $0.00015 | $0.00124 |
Grade A, and why
session-review 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 yesterday.
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.
This is a copy
100% identical to session-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Review — the adversarial closing loop
Stress-test a session's work before it sets, using reviewers who don't share your blind spots. You wrote the work, so you are the worst person to spot what you assumed. The loop ends in action: cheap-safe fixes applied immediately, the rest recorded as a measurable plan, and anything you disagree with explicitly challenged — not silently accepted, not silently dropped.
Invocation is usually EXPLICIT (/session-review) — "review" is something the agent does
natively, so don't expect auto-triggering; invoke it by name at session close.
The loop
1. Assemble the brief (the load-bearing step)
Write ONE self-contained markdown brief (e.g. to /tmp/<repo>-session-review.md). It is the
only context the reviewers get. It must contain:
- An assigned role that fits the work ("Principal Engineer" for a feature slice, "Security reviewer" for auth work) — the role is the lens.
- Project context a stranger can follow, the session goal, and what was built, with concrete file:line references.
- The specific decision points you most want challenged — and for anything that turns on CURRENT best practice, an explicit ask to web-check with sources.
- What to return — a structured verdict with severity, file refs, a short MEASURABLE plan.
Never let the brief be the reviewer's only window: tell the code-reader explicitly "do not trust this summary — read the actual files." Your summary is where your blind spots live.
2. Run the reviewers IN PARALLEL (same message)
- Reviewer A — the isolated code-reader. Spawn
idea-validatorpointed at the brief AND the actual files, with the currency instruction: "web-check whether every library / runtime / pattern I chose is still the right choice this year, cite sources." Without that line it only verifies claims you explicitly made — dated tech slips through. - Reviewer B — an external-family model (if available), reviewing from the brief only. Different training distribution, different blind spots; lean on it for concept and tech-currency, not file-level facts.
- One reviewer alone (A) is still a valid light review — note the absence and proceed.
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.
- yesterday First seen · 91 lines · 149 tokens per session scan A 29853e51633e
session-review is a skill published in the GitHub repository awrshift/agent-memory-kit (31 stars, last pushed yesterday), licensed MIT. It adds 149 tokens to every session and 1,242 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to session-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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Triage each insight into discard/code-fix/prompt-fix and produce a prioritized action plan with specific recommendations. Trigger when the user says "run stage 5", "make action plan", "triage skills", or when invoked by the kayba-pipeline orchestrator. Requires eval outputs from stages 1-4.
kayba-stage-2-domain-context
Gather domain context about the repository and agent — system prompt, tool definitions, domain docs, and behavior patterns from traces. Trigger when the user says "run stage 2", "gather context", "domain context", or when invoked by the kayba-pipeline orchestrator.
kayba-stage-1-api-analysis
Fetch pre-computed insights from the Kayba API and build a structured summary. Does NOT upload traces or trigger generation — analysis is assumed to already exist. Trigger when the user says "run stage 1", "get insights", "fetch skills", "kayba analyze", or when invoked by the kayba-pipeline orchestrator. Requires the…
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