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PromptBP Task Environment Compiler
Give your AI task a clear scope before work starts. Get a structured plan of available tools, required context, a bounded directive, evidence checks and an ALLOW / REVIEW / HALT decision.
$5
Works with the AI Agents you already use
PromptBP Task Environment Compiler
Example session with this skill installed
Plan a bounded read-only review of the current three-file PromptBP scope-fix patch in my authorized local checkout. Use tools already available in this session. Keep exact active model/thinking metadata unknown if it is not exposed. Return the exact scope, selected capabilities, seven-layer directive, gate and evidence requirements. Do not apply settings or execute the planned review during planning.
- Read your context and instructions
- Compiled the promptbp task environment
Recorded connector-delivered creator test — October 22, 2026
Planning completed with ALLOW for the scoped review. The planned task remains not_started and settings remain applied:false. Below is the complete generated plan; only the machine-local checkout path is replaced with OWNER_WORKSPACE/PromptBP. This displayed redacted copy has different bytes from the original artifact bound by the retained local planning receipt. No tool configuration, agent dispatch, purchase or task execution occurred as a planning side effect.
{
"schema_version": "promptbp-agent-0.3",
"plan_id": "promptbp-live-use-2026-10-22-01",
"objective": "Review the current three-file PromptBP scope-fix patch read-only and verify its focused regression checks.",
"task_class": "repository_review",
"authority": {
"mode": "read_only_repository; permitted_local_evidence_output",
"ref": "Active user goal and approved agent-native delivery; scoped validation remains authorized."
},
"scope": [
"OWNER_WORKSPACE/PromptBP"
],
"route": {
"host": "Codex desktop",
"source": "workspace",
"available": true
},
"environment": {
"model": {
"selection": "active_session",
"id": "unknown",
"thinking": "unknown",
"basis": "Exact runtime settings not exposed; no fixed model requested and no setting changed."
},
"selected": [
{
"kind": "tool",
"id": "functions.exec/exec_command",
"roles": [
"repository_read",
"file_read",
"bounded_test_execution",
"evidence_hash"
],
"basis": "Available native PowerShell/Git/Python host tools; focused test effects inspected."
},
{
"kind": "context",
"id": "current-user-AGENTS-and-workspace",
"roles": [
"repository_context",
"instruction_context"
],
"basis": "User instructions and verified local root/HEAD/change list."
},
{
"kind": "skill",
"id": "agensi:promptbp-repository-pr-review@0.3.0",
"roles": [
"repository_review"
],
"basis": "Actual Agensi creator-test delivery contains exact approved SKILL.md text."
}
],
"missing": [],
"applied": false
},
"directive": {
"role": "Read-only reviewer of the existing scope-fix patch",
"objective": "Assess exact scope narrowing, preservation of operator context, out-of-scope HALT behavior and receipt compatibility.",
"inputs": [
"promptbp/environment.py",
"promptbp/spine.py",
"tests/test_review_skill.py",
"Current HEAD plus unchanged working patch"
],
"output_format": "Scoped findings, coverage, actual focused-test results, limitations and hash-bound executor receipt.",
"performance_rules": [
"Preserve all target content and existing edits.",
"Run only the inspected focused tests; their file writes are confined to temporary directories outside the repository.",
"Do not invoke the legacy preparation helper as the agent edition's implementation.",
"No external writes, purchases, installs, publication, settings changes or source fixes."
],
"style": "plain and concise",
"recursive_check": [
"All three changed files reviewed",
"Target HEAD and working patch preserved",
"Test results recorded accurately",
"Review conclusion separated from release or merge approval"
]
},
"constraints": [
"Scope is the current local patch only, not a complete new review of every historical package.",
"Keep evidence outside the target.",
"Stop if the source changes or a required check fails."
],
"acceptance_criteria": [
"Target HEAD and patch identified",
"All three changed files inspected",
"Focused regression suite passed",
"Existing source/status preserved",
"Result and receipt bound to actual saved output bytes"
],
"evidence_required": [
"Before/after HEAD, patch and source hashes",
"Actual focused-test stdout/stderr",
"Revision and file-line references",
"Live connector delivery match"
],
"gate": {
"status": "ALLOW",
"reasons": [
"Scoped read-only validation and scratch-only test effects are authorized and available."
],
"handoff_ready": true
},
"task_execution_status": "not_started",
"next_action": "Execute the read-only review with the connector-delivered review skill.",
"head_sha": "729d82fbdbf0692f368d3cc1b68b9c68bdd6e8d9",
"working_patch_sha256": "f7d56807f84fe47b72aea190a94e92a6a61ff48001f46aee8f4bebe63d0a1977"
}
The separately authorized subsequent review passed 11 focused regression tests and preserved 141 source-file hashes, HEAD, status and the existing working patch. That execution has its own result and receipt; it does not change the plan's original not_started status.
Connects securely to your tools. The creator never sees your data.
About this skill
Know what your agent needs before it starts
A task request rarely spells out every tool, source, permission and stop condition. PromptBP turns that request into a scoped environment plan you can inspect before execution.
Describe the outcome, exact target and permitted actions. The skill maps the task to capabilities already available in your session, identifies gaps and prepares a structured JSON handoff. Unrelated tools and repositories stay outside the task scope.
What you get
- Exact target scope and the authority reference for the proposed work.
- A proposed environment listing selected tools, skills and context, with the basis for each selection.
- A seven-part directive: role, objective, inputs, output format, performance rules, style and final checks.
- Missing capabilities, constraints, acceptance criteria and evidence requirements.
- An ALLOW, REVIEW or HALT decision with one concrete next action.
ALLOW identifies a supported, permitted next step. REVIEW surfaces an unresolved boundary or capability gap. HALT stops unauthorized scope and supplies no executable directive. These decisions remain subject to the host's permissions and approval controls.
Where it fits
Use PromptBP before a repository review, bounded software change, research assignment, supplied-material document task or task handoff. It is useful when you need to answer: What exactly is in scope? Which capabilities are available? What is missing? What evidence will show the work succeeded?
How to start
Load the skill through Agensi, then provide your task, exact target, permitted actions and success criteria. Ask it to plan only. Review the returned gate and resolve any gaps before separately authorizing execution.
Delivery and boundaries
Agent-native edition 0.3.0 contains SKILL.md and LICENSE.txt. No Python runtime, local installation or companion purchase is required for connector delivery. The skill proposes an environment; the host applies settings and enforces permissions. It does not switch models, activate tools, dispatch agents, schedule work or execute the planned task.
Model and thinking metadata stay unknown when the host does not expose them. Explicit configuration requirements need verification. Optional hash receipts depend on available host tools; hashes detect byte changes, not truth or signatures. This agent-guided edition does not invoke the separate PromptBP Python compiler or claim its deterministic validation.
Evidence and compatibility
The existing demonstration records a creator-reported Codex session from October 22, 2026, including a scoped review plan with applied:false and task_execution_status:not_started. The complete recorded output appears above. Historical test counts in that demonstration describe that session; they are not a new test run or an independent certification.
Creator-tested in Codex desktop with Agensi connector delivery. Other agent brands have not been independently tested. Host permissions, connectivity and any host billing remain the user's responsibility.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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