Agent-almanac add-puzzle-type
git clone https://github.com/pjt222/agent-almanac
T=$(mktemp -d) && git clone --depth=1 https://github.com/pjt222/agent-almanac "$T" && mkdir -p ~/.claude/skills && cp -r "$T/i18n/caveman/skills/add-puzzle-type" ~/.claude/skills/pjt222-agent-almanac-add-puzzle-type-17cbe6 && rm -rf "$T"
i18n/caveman/skills/add-puzzle-type/SKILL.mdAdd Puzzle Type
Scaffold new puzzle type across all pipeline integration points in jigsawR.
When Use
- Adding completely new puzzle type to package
- Following established integration checklist (CLAUDE.md 10-point pipeline)
- Ensuring nothing missed when wiring new type end-to-end
Inputs
- Required: New type name (lowercase, e.g.
)"triangular" - Required: Geometry description (how pieces shaped/arranged)
- Required: Whether type needs external packages (add to Suggests)
- Optional: Parameter list beyond standard (grid, size, seed, tabsize, offset)
- Optional: Reference implementation or algorithm source
Steps
Step 1: Create Core Puzzle Module
Create
R/<type>_puzzle.R with internal generation function:
#' Generate <type> puzzle pieces (internal) #' @noRd generate_<type>_pieces_internal <- function(params, seed) { # 1. Initialize RNG state # 2. Generate piece geometries # 3. Build edge paths (SVG path data) # 4. Compute adjacency # 5. Return list: pieces, edges, adjacency, metadata }
Follow pattern in
R/voronoi_puzzle.R or R/snic_puzzle.R for structure.
Got: Function returns list with
$pieces, $edges, $adjacency, $metadata.
If fail: Compare return structure against
generate_voronoi_pieces_internal() to identify missing list elements or incorrect types.
Step 2: Wire into jigsawR_clean.R
Edit
R/jigsawR_clean.R:
- Add
to"<type>"
vectorvalid_types - Add type-specific parameter extraction in params section
- Add validation logic for type-specific constraints
- Add filename prefix mapping (e.g.,
->"<type>"
)"<type>_"
# In valid_types valid_types <- c("rectangular", "hexagonal", "concentric", "voronoi", "snic", "<type>")
Got:
generate_puzzle(type = "<type>") accepted without "unknown type" error.
If fail: Verify type string added to
valid_types exactly as spelled, parameter extraction covers all required type-specific arguments.
Step 3: Wire into unified_piece_generation.R
Edit
R/unified_piece_generation.R:
- Add dispatch case in
generate_pieces_internal() - Add fusion handling if type supports PILES notation
# In the switch/dispatch "<type>" = generate_<type>_pieces_internal(params, seed)
Got: Pieces generated when type dispatched.
If fail: Confirm dispatch case string matches type name exactly.
generate_<type>_pieces_internal defined and exported from puzzle module.
Step 4: Wire into piece_positioning.R
Edit
R/piece_positioning.R:
Add positioning dispatch for new type. Most types use shared positioning logic. Some need custom handling.
Got:
apply_piece_positioning() handles new type without errors. Pieces placed at correct coordinates.
If fail: Check whether new type needs custom positioning logic or can reuse shared positioning path. Add dispatch case if default path does not apply.
Step 5: Wire into unified_renderer.R
Edit
R/unified_renderer.R:
- Add rendering case in
render_puzzle_svg() - Add edge path function:
get_<type>_edge_paths() - Add piece name function:
get_<type>_piece_name()
Got: SVG output generated for new type with correct piece outlines and edge paths.
If fail: Verify
get_<type>_edge_paths() returns valid SVG path data. get_<type>_piece_name() produces unique identifiers for each piece.
Step 6: Wire into adjacency_api.R
Edit
R/adjacency_api.R:
Add neighbor dispatch so
get_neighbors() and get_adjacency() work for new type.
Got:
get_neighbors(result, piece_id) returns correct neighbors for any piece in puzzle.
If fail: Check adjacency dispatch returns correct data structure. Test with small grid and manually verify neighbor relationships against geometry.
Step 7: Add ggpuzzle Geom Layer
Edit
R/geom_puzzle.R:
Create
geom_puzzle_<type>() using make_puzzle_layer() factory:
#' @export geom_puzzle_<type> <- function(mapping = NULL, data = NULL, ...) { make_puzzle_layer(type = "<type>", mapping = mapping, data = data, ...) }
Got:
ggplot() + geom_puzzle_<type>(aes(...)) renders without error.
If fail: Verify
make_puzzle_layer() receives correct type string. Geom function exported in NAMESPACE via @export.
Step 8: Add Stat Dispatch
Edit
R/stat_puzzle.R:
- Add type-specific default parameters
- Add dispatch case in
compute_panel()
Got: Stat layer computes puzzle geometry correctly. Produces expected number of polygons.
If fail: Check
compute_panel() dispatch case returns data frame with required columns (x, y, group, piece_id). Default parameters sensible for new type.
Step 9: Update DESCRIPTION
Edit
DESCRIPTION:
- Add new type to Description field text
- Add any new packages to
(if external dependency)Suggests: - Update
to include new R file (alphabetical order)Collate:
Got:
devtools::document() succeeds. No NOTE about unlisted files.
If fail: Check new R file listed in
Collate: field in alphabetical order. Any new Suggests packages spelled correctly with version constraints.
Step 10: Update config.yml
Edit
inst/config.yml:
Add defaults and constraints for new type:
<type>: grid: default: [3, 3] min: [2, 2] max: [20, 20] size: default: [300, 300] min: [100, 100] max: [2000, 2000] tabsize: default: 20 min: 5 max: 50 # Add type-specific params here
Got: Config valid YAML. Defaults produce working puzzle when used by
generate_puzzle().
If fail: Validate YAML with
yaml::yaml.load_file("inst/config.yml"). Ensure default grid and size values produce sensible puzzle (not too small or too large).
Step 11: Extend Shiny App
Edit
inst/shiny-app/app.R:
- Add new type to UI type selector
- Add conditional UI panels for type-specific parameters
- Add server-side generation logic
Got: Shiny app shows new type in dropdown. Generates puzzles when selected.
If fail: Check type added to
choices argument of UI selector. Conditional panel for type-specific parameters uses conditionalPanel(condition = "input.type == '<type>'"). Server-side handler passes correct parameters.
Step 12: Create Test Suite
Create
tests/testthat/test-<type>-puzzles.R:
test_that("<type> puzzle generates correct piece count", { ... }) test_that("<type> puzzle respects seed reproducibility", { ... }) test_that("<type> adjacency returns valid neighbors", { ... }) test_that("<type> fusion merges pieces correctly", { ... }) test_that("<type> geom layer renders without error", { ... }) test_that("<type> SVG output is well-formed", { ... }) test_that("<type> config constraints are enforced", { ... })
Type requires external package? Wrap tests with
skip_if_not_installed().
Got: All tests pass. No skips unless external dependency missing.
If fail: Check each integration point individually. Most common issue: missing dispatch cases — run
grep -rn "switch\|valid_types" R/ to find all dispatch locations.
Checks
-
produces valid outputgenerate_puzzle(type = "<type>") - All 10 integration points wired correctly
-
passes with new testsdevtools::test() -
returns 0 errors, 0 warningsdevtools::check() - Shiny app renders new type
- Config constraints enforced (min/max validation)
- Adjacency and fusion work correctly
- ggpuzzle geom layer renders without error
-
succeeds (NAMESPACE updated)devtools::document()
Pitfalls
- Missing dispatch case: Forgetting one of 10+ files causes silent failure or "unknown type" errors
- strsplit with negative numbers: Creating adjacency keys with
? Negative piece labels produce keys likepaste(a, b, sep = "-")
. Use"1--1"
separator instead. Split with"|"
."\\|" - Using
for output: Always usecat()
package logging wrappers (cli
,log_info
, etc.)log_warn - Collate order: DESCRIPTION Collate field must be alphabetical or dependency-ordered
- Config.yml format: Ensure YAML valid; test with
yaml::yaml.load_file("inst/config.yml")
See Also
— test new type after scaffoldinggenerate-puzzle
— run full test suite to verify integrationrun-puzzle-tests
— test fusion with new typevalidate-piles-notation
— general test-writing patternswrite-testthat-tests
— document new geom functionwrite-roxygen-docs