Register with Custodian State Hub and seed format open-questions workplan

Register canned-prompts under agents / practice (topic
c1d199b6-55ee-4db6-b49e-257a9f0f15ac, workplan prefix CANP-WP) via
`statehub register`, then replace the generated placeholders with
repo-specific facts.

- SCOPE.md: real boundaries drawn from INTENT.md's deliberate boundary,
  current state (spec v0.1 + reference CLI, 3/3 tests pass, example
  round-trips), and the developer workflow.
- AGENTS.md: drop the unresolved {CREDENTIAL_ROUTING} template token left
  by the generator.
- CANP-WP-0001: bootstrap tasks closed.
- CANP-WP-0002: new workplan carrying the five § 23 open questions promoted
  from "experience will decide" to "decide for v0.2" — optional-input
  defaults (static or derived), registry namespaces/ownership, prompt
  composition, canonical eval schemas, typed context/dependency contracts —
  plus two reference-implementation conformance defects found in review
  (prerelease versions sort as newest; copy_immutable packages the whole
  source directory).

Also lands the previously untracked seed: INTENT.md, the CPF v0.1 spec,
the reference CLI, and examples/pqrst-estimate.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Bjefh8NUiEiahN4JLwoSKM

Assistant: claude-code
Assistant-Model: opus
Assistant-Process: 388925@bnt-lap001
Assistant-Session: 3507023f-e0fd-4a1e-9d90-a0d4217d1502
This commit is contained in:
tegwick 2026-09-06 00:45:23 +02:00
parent 985b41dc87
commit dc615ef530
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# PQRST Estimate example
This package is included as a first non-trivial example of Canned Prompt Format v0.1.
It demonstrates:
- one required content input;
- one boolean parameter with a default;
- a structured output expectation;
- discovery tags;
- a prompt that carries terminology and interpretation rules, not merely prose.

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name: feature implementation with unfamiliar codebase
values:
session_summary: |
The session traced an unfamiliar request path through the repository,
implemented a new validation rule, added unit and integration tests, fixed
two edge cases discovered during testing, and updated the implementation
after finding a conflicting assumption in an internal helper.
include_rationale: true

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Review the coding session described below and produce a **PQRST Estimate** of
where effort was spent.
Use these categories:
- **P — Main problem:** implementing or directly solving the requested deliverable.
- **Q — Quality and tests:** tests, verification, edge cases, maintainability,
error handling, cleanup, and production-quality hardening.
- **R — Research and context clarification:** reading the codebase or docs,
tracing behavior, investigating unknowns, reconciling requirements, and
establishing missing context.
- **S — Security and credentials:** authentication, authorization, secrets,
credentials, trust boundaries, security validation, and security-specific
handling.
- **T — Task organization:** planning, decomposition, todo management,
sequencing, coordination, and overhead required to keep the work organized.
Treat this as a **post-session audit, not a planning estimate**. Estimate
relative cognitive/work effort rather than tokens or wall-clock time. The five
percentages **must sum to exactly 100%**.
Where activities overlap, assign effort according to the primary purpose of the
activity. Do not inflate a category merely because it was important; estimate
how much effort it actually consumed.
Session material:
{{ session_summary }}
Return:
```text
P: NN%
Q: NN%
R: NN%
S: NN%
T: NN%
Total: 100%
```
Then provide:
1. **Primary effort driver** — one sentence naming what dominated the session.
2. **Interpretation** — what the distribution says about the session's shape.
3. **Signal** — one notable imbalance, if any, that may be worth learning from.
Include rationale: {{ include_rationale }}

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format: canned-prompt/v0.1
id: practice/pqrst-estimate
name: PQRST Estimate
version: 0.1.0
summary: 'Produce a post-session estimate of effort distributed across the PQRST categories
for an agentic coding session.
'
type: template
template: prompt.md
inputs:
- name: session_summary
type: content
required: true
description: 'Session transcript, summary, or sufficiently detailed account of the
work performed during the coding session.
'
parameters:
include_rationale:
type: boolean
default: true
description: Explain the evidence behind the estimate.
output:
format: markdown
description: A 100% PQRST effort allocation with concise interpretation.
compatibility:
capabilities:
- session-review
tags:
- pqrst
- retrospective
- agentic-coding
- effort-estimation
provenance:
author: canned-prompts seed
examples:
- examples/basic.yaml