lab-helper
Skill397 starsChanged 11 days agoApache-2.0View on GitHub
Diagnoses workspace drift across Modules 1 to 4 of the Pitch Generator lab, delivers progressive 3-tier hints, and restores reference step implementations when hints are exhausted. Use when a learner asks for a hint, gets stuck on a lab step, wants to verify their workspace against a module solution, or requests workspace remediation.
In this repository79 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
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- Common
- Distinctive
- Very specific
- Distinctive: line 20
When the learner sends prompts such as:
- Very specific: line 35
Run the verification script using run_command:
- Very specific: line 43
If Remediation is requested: Read the reference file in .agents/solutions/ and surgically patch pitch_generator/ in-place at the …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Pitch Generator Lab Helper Skill
The Lab Helper skill provides an interactive, pedagogical diagnosis and recovery engine for learners working through the Pitch Generator lab (bwg001-devlab-1b). It actively inspects the learner's workspace directory against the 9 reference solution steps across Modules 1–4, assesses syntactic and structural drift, delivers calibrated educational guidance, and safely restores files if a learner gets stuck.
Conversational & Prompt-Driven Interaction
The learner interacts with this skill entirely through natural conversation in the Antigravity chat panel. The learner does not need to run terminal verification commands or remember CLI flags.
1. Handling Learner Inquiries (Strictly On-Demand)
Important: Only invoke this skill on-demand when the learner explicitly asks to verify a step, requests a hint, or asks for help fixing a stuck step. Never run verification or read
.agents/solutions/while implementing a normal feature prompt.
When the learner sends prompts such as:
- "I can't get step 2a working properly, can you give me a hint?"
- "Please verify I completed step 1a correctly"
- "Can I have another hint?"
- "I am completely stuck on step 3c, please help me fix it"
The assistant follows this multi-step protocol:
- Step Identification: Identify the module and step referenced in the user's prompt (for example,
step 2amaps to Module 2, Step 2a). If the user asks generally ("verify step 2"), inspect the workspace to identify the active step. - Contextual Tier Tracking: Inspect the recent conversation history to determine which hint tier to provide:
- First inquiry on a step (e.g., "give me a hint" or "verify step 1a"): Use Tier 1 (Conceptual Nudge).
- Follow-up request (e.g., "can I have another hint?" or "need more detail"): Advance to Tier 2 (Targeted File & Symbol Hint).
- Second follow-up (e.g., "still stuck, another hint?"): Advance to Tier 3 (Implementation Blueprint & Code Snippet).
- Exhausted hints or explicit remediation request (e.g., "please bring my workspace into a working state"): Use In-Place Remediation to patch the step into
pitch_generator/.
- Execute Diagnostic & Semantic Intent Comparison:
- Run the verification script using
run_command:python3 .agents/skills/lab-helper/scripts/verify_workspace.py --module <M> --step <S> --tier <T> --json - Semantic Intent Allowance: If
verify_workspace.pyreports a missing helper symbol, compare the learner's code inpitch_generator/against the corresponding.agents/solutions/reference file. If the learner's code achieves the same architectural intent and runtime behavior (with only benign differences in local variable names, helper function names, or instruction phrasing), treat the step as completed and congratulate the learner!
- Run the verification script using
- Interpret Output & Formulate Response:
- If completed (
drift_detected: falseor semantically equivalent): Congratulate the learner, confirm that their implementation meets the step's architectural goal, and briefly summarize what they accomplished. - If substantive drift is detected: Present the progressive hint corresponding to the current tier (see TEMPLATES.md). Explain the architectural rationale ("why") and encourage the learner to iterate.
- If Remediation is requested: Read the reference file in
.agents/solutions/and surgically patchpitch_generator/in-place at the corresponding# [Guidepost — Step <id>]block. Never overwrite cumulative files (pitch_generator/agent.pyorpitch_generator/app_utils/services.py) wholesale, so earlier steps, user customizations, and remaining guidepost comments for future steps are preserved.
- If completed (
Progressive 3-Tier Hint & In-Place Remediation Protocol
To ensure learners build genuine understanding without having solutions spoiled prematurely, Lab Helper enforces a deterministic 3-tier progressive hint protocol:
- Tier 1 — Conceptual Nudge:
- Offers an architectural "why" explanation and high-level conceptual nudge.
- Highlights the core design pattern (for example, ADK single-responsibility agents, JoinNode fan-in, PreToolUse policy hooks).
- Strictly read-only: does not disclose specific file paths, code snippets, or modify workspace files.
- Tier 2 — Targeted File & Symbol Hint:
- Identifies the exact target file path relative to the workspace root.
- Details required classes, functions, AST symbols, interface signatures, or schema keys.
- Highlights missing tokens without writing code or modifying learner files.
- Tier 3 — Concrete Implementation Blueprint:
- Delivers a concrete implementation blueprint and minimal idiomatic code snippet illustrating how to resolve the drift.
- Explains parameter bindings, edge cases, and verification commands.
- Strictly read-only: does not overwrite any learner files.
- In-Place Surgical Remediation:
- Used when hints are exhausted or the learner explicitly asks to fix/restore a step.
- For cumulative files (
pitch_generator/agent.py,pitch_generator/app_utils/services.py,pitch_generator/fast_api_app.py), read the reference solution in.agents/solutions/and patch the missing/broken step code in-place, preserving all prior steps and future# [Guidepost — ...]comments. - For standalone files (
pitch_generator/skills/brand-guidelines/SKILL.md,pitch_generator/sql/*.sql), restore or create the file from.agents/solutions/.
Supported Modules and Steps (1a–4a)
Lab Helper supports all 9 progressive steps across the 4 syllabus modules:
| Module | Step ID | Step Title & Description | Target Deliverable(s) (Application & Reference) |
| Module 1 | 1a | Authoring Agent Skills (brand-guidelines) | pitch_generator/skills/brand-guidelines/SKILL.md, pitch_generator/agent.py (ref: module_1/step_1a_authoring_skills.py) |
1b | Skill Evaluation Harnesses | tests/test_module_1.py / pitch_generator/ (ref: module_1/step_1b_skill_evals.py) | |
1c | Remote A2A Visual Director Service | pitch_generator/agent.py, pitch_generator/fast_api_app.py (ref: module_1/step_1c_remote_a2a_visual_director.py) | |
| Module 2 | 2a | BigQuery Agent Analytics & Key Visuals Object Table | pitch_generator/app_utils/services.py (ref: module_2/step_2a_bigquery_analytics.py, sql/create_key_visuals.sql) |
2b | Brand Drift Detection & Closed-Loop Prompt Tuning | pitch_generator/app_utils/services.py (ref: module_2/step_2b_drift_detection_and_tuning.py, sql/score_brand_fit.sql) | |
| Module 3 | 3a | PreToolUse Lifecycle Policy Hooks | pitch_generator/agent.py (ref: module_3/step_3a_pre_tool_use_hooks.py) |
3b | PII Data Scrubbing & Redaction | pitch_generator/app_utils/services.py (ref: module_3/step_3b_pii_scrubbing.py) | |
3c | Human-in-the-Loop (HITL) Authorizations | pitch_generator/agent.py (ref: module_3/step_3c_hitl_authorizations.py) | |
| Module 4 | 4a | Tokenomics & History Optimization | pitch_generator/agent.py (ref: module_4/step_4a_tokenomics.py) |
Running the Workspace Verification Script
The underlying diagnostic engine is implemented in scripts/verify_workspace.py and executed by the assistant via CLI commands:
1. Requesting Progressive Hints (Read-Only)
# Tier 1 Conceptual Nudge
python3 .agents/skills/lab-helper/scripts/verify_workspace.py --module 1 --step 1a --tier 1 --json
# Tier 2 Targeted File & Symbol Hint
python3 .agents/skills/lab-helper/scripts/verify_workspace.py --module 1 --step 1a --tier 2 --json
# Tier 3 Implementation Blueprint
python3 .agents/skills/lab-helper/scripts/verify_workspace.py --module 1 --step 1a --tier 3 --json2. Auto-Remediating a Stuck Step
# Restore step files to bring workspace to 0 drift
python3 .agents/skills/lab-helper/scripts/verify_workspace.py --module 1 --step 1a --tier remediate --json3. Inspecting the Entire Workspace
# Verify all steps across all 4 modules
python3 .agents/skills/lab-helper/scripts/verify_workspace.py --step all --jsonReference Documentation
- See REFERENCE.md for the detailed step rubrics, AST symbols, CLI flags, exit codes, and JSON response schema.
- See TEMPLATES.md for the standardized educator response formatting templates for Tiers 1–3 and auto-remediation.
- Structured hint data and drift rules are maintained in
references/hints_catalog.jsonand consumed byscripts/verify_workspace.py.
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