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kitaru-replay-ops

decode's Kitaru operator surface for headless replay and what-if — three-runs (observed / baseline-rerun / fork), CLI replay with --args/--overrides, checkpoint overrides, diffing execution records, cohort scaling, wait re-ask behavior, subagent-as-one-checkpoint. Use when replay

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Headless replay & what-if (Kitaru operator surface — documented, not wrapped)

decode replay wraps only the bypass model-swap common case, 1:1 over Kitaru's native flow-object replay (ADR-0010 §5). Full checkpoint → replay → diff → decide loop = Kitaru's own CLI/SDK — decode deliberately does not re-implement diff, cohort, or checkpoint-override machinery (ADR-0010 §6). Below: that operator surface, verified against installed kitaru 0.18 + docs.zenml.io ("Replay and Overrides", "Replay and improve"); patterns / roadmap items flagged as such.

Three runs, not two. Trustworthy what-if = three runs; the middle is the point:

Run	What it is	Role
Observed	original recorded run	what actually happened
Baseline Rerun	`kitaru executions replay <id> --from <cp>`, no change	control — proves replay reproduces faithfully
Fork	same `--from`, one input changed (e.g. `--args '{"model":…}'`)	your change

Diff Fork vs Baseline Rerun, not vs Observed — the control isolates your one variable. Baseline Rerun ≠ Observed (nondeterministic tool, external state, time)? Diff untrustworthy; pin the nondeterminism first.

CLI replay with overrides (surface decode replay --model wraps a slice of):

kitaru executions replay <exec_id> --from <cp>                                   # Baseline Rerun (control)
kitaru executions replay <exec_id> --from <cp> --args '{"model":"gemini-2.5-pro"}'   # Fork (flow-input swap)
kitaru executions replay <exec_id> --from <cp> --overrides '{"checkpoint.<name>":<value>}'  # checkpoint-output swap

--args = flow-input overrides (CLI mirror of flow.replay(..., model=…); decode replay --model surfaces this). The Model Override rides here.
--overrides checkpoint.<name> = Checkpoint Override: substitute a recorded checkpoint's single output at its direct consumers, re-executing from there forward. Keys must start with checkpoint. (else KitaruUsageError); overridden checkpoint must expose a single output.
--overrides checkpoint.X = the tool-output mock stand-in. Per-tool-call output= / raise_= mocks (fake value / forced failure) are Kitaru roadmap, not shipped — ZenML guide flags this. Today: override the tool's recorded checkpoint output.

Diff = compare the two execution records. No kitaru diff CLI, no .diff() SDK method in kitaru 0.18 (verified — do not assume one). Manual comparison; the ZenML guide's own pattern:

kitaru executions get <fork_exec_id>        # decision, per-checkpoint outputs, cost, latency
kitaru executions get <baseline_rerun_id>   # the control to compare against

SDK: KitaruClient().executions.get(fork.exec_id) vs .get(rerun.exec_id) — compare cost/latency/decision. Baseline reproduced → any difference attributable to your one change. decode replay prints the same stderr hint (kitaru executions get <new> vs <original>), pointing only at this confirmed surface.

Cohort: scale the winning change across recent runs — example pattern on SDK primitives, NOT a core Kitaru API. ZenML "Replay and improve" guide ships run_cohort (+ cost / latency / quality_judge metric callables) in the kitaru examples repo (examples/end_to_end/pydantic_replay_fork); "not in the kitaru package — copy or adapt" (import kitaru_recipes is not an installed module — verified):

from cohort import run_cohort                 # from the EXAMPLE dir, not `import kitaru`
from utils import cost, latency, quality_judge
# exec_ids: recent runs, e.g. KitaruClient().executions.list(flow="run_agent_task")
report = run_cohort(exec_ids, baseline_model="gemini-2.5-flash",
                    variant_model="gemini-2.5-pro", metrics=[cost, latency, quality_judge])
report.summary()      # per-metric baseline-vs-variant deltas + an is-it-better verdict
report.regressions()  # the metrics / decisions that got worse

Per run: reproduce baseline, replay variant, score the pair — decide on a cohort, not one lucky run.

Waits re-ask on replay. A replayed run re-asks every wait() — Kitaru "does not support overriding or pre-populating wait results." Hence decode replay is bypass-only + HITL answer-reuse deferred (see replay row above). Honesty note: on a decode run --hitl pause, Kitaru itself prints Waiting for input… to stdout (framework behavior) — the pipe-clean guarantee covers the completed bypass answer only.

A subagent run = one opaque checkpoint. A whole agent(...) spawn — the child's entire nested loop — is one opaque tool call → one checkpoint under "calls": nested child model calls are not replay anchors; a decode replay --model swap does not reach inside a child (child rides parent's model — AgentDef has no model field). Read-only child's cached summary is replay-safe → agent never joins the sandbox-bash cache-disable set; child token spend stays folded into that one tool call, invisible until Opik (M10) — ADR-0013 §9.

An agent can drive the whole loop. Kitaru exposes this replay surface over an MCP server (kitaru-mcp console script) — a coding agent (Claude Code, Codex, Cursor) can pull a recent run, propose a change, replay vs control, compare, widen to a cohort — future automation hook (no decode work now).

Lihat sumber ↗

Metadata berkas

name: kitaru-replay-ops
description: decode's Kitaru operator surface for headless replay and what-if — three-runs (observed / baseline-rerun / fork), CLI replay with --args/--overrides, checkpoint overrides, diffing execution records, cohort scaling, wait re-ask behavior, subagent-as-one-checkpoint. Use when replaying or forking a decode run, overriding checkpoints, or comparing executions with the kitaru CLI/SDK.

Lihat teks asli

---
name: kitaru-replay-ops
description: decode's Kitaru operator surface for headless replay and what-if — three-runs (observed / baseline-rerun / fork), CLI replay with --args/--overrides, checkpoint overrides, diffing execution records, cohort scaling, wait re-ask behavior, subagent-as-one-checkpoint. Use when replaying or forking a decode run, overriding checkpoints, or comparing executions with the kitaru CLI/SDK.
---

## Headless replay & what-if (Kitaru operator surface — documented, not wrapped)

`decode replay` wraps only the **bypass model-swap** common case, 1:1 over Kitaru's native flow-object replay (ADR-0010 §5). Full **checkpoint → replay → diff → decide** loop = Kitaru's own CLI/SDK — decode deliberately does **not** re-implement diff, cohort, or checkpoint-override machinery (ADR-0010 §6). Below: that operator surface, verified against installed **kitaru 0.18** + docs.zenml.io ("Replay and Overrides", "Replay and improve"); patterns / roadmap items flagged as such.

**Three runs, not two.** Trustworthy what-if = three runs; the middle is the point:

| Run | What it is | Role |
|---|---|---|
| **Observed** | original recorded run | what actually happened |
| **Baseline Rerun** | `kitaru executions replay <id> --from <cp>`, **no** change | *control* — proves replay reproduces faithfully |
| **Fork** | same `--from`, **one** input changed (e.g. `--args '{"model":…}'`) | your change |

Diff **Fork vs Baseline Rerun**, not vs Observed — the control isolates your one variable. Baseline Rerun ≠ Observed (nondeterministic tool, external state, time)? Diff untrustworthy; pin the nondeterminism first.

**CLI replay with overrides** (surface `decode replay --model` wraps a slice of):

```bash
kitaru executions replay <exec_id> --from <cp>                                   # Baseline Rerun (control)
kitaru executions replay <exec_id> --from <cp> --args '{"model":"gemini-2.5-pro"}'   # Fork (flow-input swap)
kitaru executions replay <exec_id> --from <cp> --overrides '{"checkpoint.<name>":<value>}'  # checkpoint-output swap
```

- `--args` = **flow-input** overrides (CLI mirror of `flow.replay(..., model=…)`; `decode replay --model` surfaces this). The **Model Override** rides here.
- `--overrides checkpoint.<name>` = **Checkpoint Override**: substitute a recorded checkpoint's single output at its **direct consumers**, re-executing from there forward. Keys **must** start with `checkpoint.` (else `KitaruUsageError`); overridden checkpoint must expose a single output.
- **`--overrides checkpoint.X` = the tool-output mock stand-in.** Per-tool-call `output=` / `raise_=` mocks (fake value / forced failure) are **Kitaru roadmap, not shipped** — ZenML guide flags this. Today: override the tool's recorded checkpoint output.

**Diff = compare the two execution records.** **No `kitaru diff` CLI, no `.diff()` SDK method in kitaru 0.18** (verified — do not assume one). Manual comparison; the ZenML guide's own pattern:

```bash
kitaru executions get <fork_exec_id>        # decision, per-checkpoint outputs, cost, latency
kitaru executions get <baseline_rerun_id>   # the control to compare against
```

SDK: `KitaruClient().executions.get(fork.exec_id)` vs `.get(rerun.exec_id)` — compare cost/latency/decision. Baseline reproduced → any difference attributable to your one change. `decode replay` prints the same stderr hint (`kitaru executions get <new> vs <original>`), pointing only at this confirmed surface.

**Cohort: scale the winning change across recent runs** — **example pattern on SDK primitives, NOT a core Kitaru API.** ZenML "Replay and improve" guide ships `run_cohort` (+ `cost` / `latency` / `quality_judge` metric callables) in the **kitaru examples repo** (`examples/end_to_end/pydantic_replay_fork`); *"not in the `kitaru` package — copy or adapt"* (`import kitaru_recipes` is **not** an installed module — verified):

```python
from cohort import run_cohort                 # from the EXAMPLE dir, not `import kitaru`
from utils import cost, latency, quality_judge
# exec_ids: recent runs, e.g. KitaruClient().executions.list(flow="run_agent_task")
report = run_cohort(exec_ids, baseline_model="gemini-2.5-flash",
                    variant_model="gemini-2.5-pro", metrics=[cost, latency, quality_judge])
report.summary()      # per-metric baseline-vs-variant deltas + an is-it-better verdict
report.regressions()  # the metrics / decisions that got worse
```

Per run: reproduce baseline, replay variant, score the pair — decide on a cohort, not one lucky run.

**Waits re-ask on replay.** A replayed run **re-asks** every `wait()` — Kitaru "does not support overriding or pre-populating wait results." Hence `decode replay` is bypass-only + HITL answer-reuse deferred (see replay row above). Honesty note: on a `decode run --hitl` **pause**, Kitaru itself prints `Waiting for input…` to **stdout** (framework behavior) — the pipe-clean guarantee covers the completed **bypass** answer only.

**A subagent run = one opaque checkpoint.** A whole `agent(...)` spawn — the child's entire nested loop — is one opaque tool call → **one** checkpoint under `"calls"`: nested child model calls are **not** replay anchors; a `decode replay --model` swap does **not** reach inside a child (child rides parent's model — `AgentDef` has no model field). Read-only child's cached summary is replay-safe → `agent` never joins the sandbox-bash cache-disable set; child token spend stays folded into that one tool call, invisible until Opik (M10) — ADR-0013 §9.

**An agent can drive the whole loop.** Kitaru exposes this replay surface over an **MCP server** (`kitaru-mcp` console script) — a coding agent (Claude Code, Codex, Cursor) can pull a recent run, propose a change, replay vs control, compare, widen to a cohort — future automation hook (no decode work now).

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Harga dan biaya penggunaan

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Lisensi: Apache-2.0
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Tinjau sebelum memasang: Hindari pemasangan otomatis

Lisensi: Apache-2.0

Dependency or permission surface needs review
Permission surface may require sandboxing
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Buka audit lengkap

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Mulai dengan tugas kecil

1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.

Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.

Sumber dan catatan penggunaan

Terindeks

Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.

Repositori sumber: decodingai-magazine/building-a-coding-agent-from-scratch-course
Lisensi: Apache-2.0
Versi: 1.0.0
Push GitHub terakhir: 3 Sep 2026
Direktori diperbarui: 5 Sep 2026
Jalur instruksi: .claude/skills/kitaru-replay-ops/SKILL.md @ 6ee643fbfeb1

Versi dilaporkan dalam metadata direktori; periksa rilis sumber.

Kualitas

69/100

Menjanjikan

Kepercayaan

64/100

Hanya sandbox

Audit

76/100

Berisiko

Buka audit lengkap Lihat laporan evaluasi

Dependency or permission surface needs review
Permission surface may require sandboxing
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Hasil: —

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Detail lainnya

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      "Permission surface may require sandboxing",
      "Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required",
      "This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 69,
    "label": "Promising"
  },
  "supply": {
    "track": "Coding and developer agents",
    "scenario": "Coding agents",
    "maintenance": "1mo since push",
    "risk": "Risky"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "high-compliance environments without internal security review",
    "No major risk signals from current metadata",
    "Audit risk risky exceeds max_risk=medium",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required"
  ],
  "agent_contract": {
    "task_input": "Use kitaru-replay-ops in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 72/100 Strong shortlist",
      "Audit: 76/100 Risky",
      "Safety: 36/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "decodingai-magazine-kitaru-replay-ops (kitaru-replay-ops)",
      "install_command": "npx skills add decodingai-magazine/building-a-coding-agent-from-scratch-course --skill kitaru-replay-ops",
      "risk_summary": "Risky; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "decodingai-magazine-kitaru-replay-ops",
      "task": "Use kitaru-replay-ops in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/decodingai-magazine-kitaru-replay-ops",
    "api": "https://www.openagentskill.com/api/agent/skills/decodingai-magazine-kitaru-replay-ops",
    "audit": "https://www.openagentskill.com/skills/decodingai-magazine-kitaru-replay-ops/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=decodingai-magazine-kitaru-replay-ops&task=Use%20kitaru-replay-ops%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20kitaru-replay-ops%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20kitaru-replay-ops%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/decodingai-magazine-kitaru-replay-ops/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/decodingai-magazine-kitaru-replay-ops"
  }
}

Untuk kreator

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator: decodingai-magazine
Sumber: decodingai-magazine/building-a-coding-agent-from-scratch-course
Diindeks oleh: Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan decodingai-magazine, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit berbagi

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/decodingai-magazine-kitaru-replay-ops?metric=listed&label=Listed)](https://www.openagentskill.com/skills/decodingai-magazine-kitaru-replay-ops?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/decodingai-magazine-kitaru-replay-ops?metric=trust&label=Trust)](https://www.openagentskill.com/skills/decodingai-magazine-kitaru-replay-ops?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/decodingai-magazine-kitaru-replay-ops?metric=audit&label=Audit)](https://www.openagentskill.com/skills/decodingai-magazine-kitaru-replay-ops/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/decodingai-magazine-kitaru-replay-ops?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/decodingai-magazine-kitaru-replay-ops?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

Pratinjau badge Buka audit Kit kreator

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.