Bird Watching Mode

Bird-watching log workflow: ask for place on enable, resolve eBird region via superpicky-cli region-query, persist to workspace/bird.json; record sightings (time, species) from user text or BirdID photo identify; export CSV summary for the user. Invocation requires absolute paths for script, --workspace, and image files. Use when the user enables 观鸟模式, bird watching mode, wants to log birds, export sightings to CSV, or record species from photos to bird.json.

Bird watching mode (观鸟模式)

Purpose

1. On enable: Ask the user for 地点 (place name). Resolve eBird region with superpicky-cli region-query, then write workspace/bird.json.
2. During use: Either identify a photo (BirdID via scripts) or record plain text (species name). Always append time + species (and optional fields) to workspace/bird.json.
3. Summary / export: On request, run export_csv.py to produce CSV (and optional per-species counts), then send the file or paste to the user (chat attachment, email, etc.).

$SKILL = directory containing this SKILL.md (usually ~/.myagent/skills/bird-watching-mode). Before invoking anything, resolve it to an absolute path (e.g. SKILL="$(cd ~/.myagent/skills/bird-watching-mode && pwd)").

Paths

• Bird log file: {project}/workspace/bird.json (create workspace/ if missing).
• SuperPicky skill: default sibling ../superpicky-cli. Override with env SUPERPICKY_CLI_SKILL (absolute path to superpicky-cli skill root).

Absolute paths (required for invocation)

When calling these scripts from the agent or shell, all filesystem arguments must be absolute paths — do not rely on cwd or ~ inside subprocesses unless the shell expands them before the call.

Argument	Rule
Python script path	Must be absolute, e.g. /Users/you/.myagent/skills/bird-watching-mode/scripts/set_region.py.
--workspace	Must be the absolute project root (directory that will contain workspace/bird.json).
Image path (identify_photo.py positional, --image on append_sighting.py)	Must be absolute path to the file on disk.
--output / --summary-output (export_csv.py)	If not -, use an absolute path for the CSV file (avoids ambiguity vs cwd).

Relative paths inside stored JSON (e.g. past image_path values) are legacy data only; new invocations should still use absolute paths.

Scripts (run from any cwd)

Script	Role
scripts/set_region.py	After user gives a place: call region-query --json, pick match, merge into bird.json (region, location_query, country_code).
scripts/append_sighting.py	Append one observation: --species, optional --notes, --source text|photo, --image, --time (ISO UTC).
scripts/identify_photo.py	Run BirdID identify using -c/-r from bird.json; print CLI stdout (agent reads top species); optional --append to log raw output + image path.
scripts/export_csv.py	Export all observations to CSV; optional --summary for per-species counts. Deliver CSV to the user (file path or - stdout for inline paste).

bash

# $SKILL and PROJECT must already be absolute (example values):
# SKILL=/Users/you/.myagent/skills/bird-watching-mode
# PROJECT=/Users/you/Workspace/myproject
# PHOTO=/Users/you/.myagent/workspace/media/abc123.jpg

# Resolve region (agent: ask user to confirm if multiple lines printed)
python3 "${SKILL}/scripts/set_region.py" --workspace "${PROJECT}" --location "上海"

# Manual / AI-confirmed text record
python3 "${SKILL}/scripts/append_sighting.py" --workspace "${PROJECT}" \
  --species "Eurasian Tree Sparrow" --source text --notes "flock of 5"

# Photo: run BirdID (requires superpicky install + models)
python3 "${SKILL}/scripts/identify_photo.py" --workspace "${PROJECT}" "${PHOTO}"
# Optional: append a sighting row with species left empty for later edit, or use --append-species "Latin name"
python3 "${SKILL}/scripts/identify_photo.py" --workspace "${PROJECT}" --append "${PHOTO}"

# Export CSV (default: workspace/bird_sightings_export.csv under PROJECT); paths printed on stderr
python3 "${SKILL}/scripts/export_csv.py" --workspace "${PROJECT}"
python3 "${SKILL}/scripts/export_csv.py" --workspace "${PROJECT}" --summary
python3 "${SKILL}/scripts/export_csv.py" --workspace "${PROJECT}" --output -   # stdout for paste only; no second file

Agent workflow

A. User turns on 观鸟模式

1. Ask: Where are you birding? (地点 — city, province, park, etc.)
2. Run set_region.py using absolute paths for the script and --workspace. If exit code 3, several matches were printed — ask the user which code (or re-run with --pick N).
3. Confirm workspace/bird.json exists and contains region.code (and country_code).

B. User sends a photo

1. Ensure SuperPicky is installed (see Prerequisites below).
2. Run identify_photo.py with absolute script path, absolute --workspace, and absolute image file path.
3. Read stdout; treat top BirdID lines as primary candidates. Confirm species with the user if uncertain.
4. Run append_sighting.py with absolute script path and --workspace, final --species, --source photo, and absolute --image path.

Prerequisites: SuperPicky venv under $SUPERPICKY_CLI_SKILL (default sibling superpicky-cli). If missing: $SUPERPICKY_CLI_SKILL/scripts/install.sh (see superpicky-cli skill).

C. User sends text (species / field note)

1. Parse species (and optional notes) from the message.
2. Run append_sighting.py with absolute script path, absolute --workspace, and --source text.

D. User asks for 汇总 / 导出 / CSV

1. Run export_csv.py with absolute script path and absolute --workspace (add --summary if they want counts by species; use absolute paths for --output / --summary-output when writing files).
2. Read the path(s) printed on stderr; attach the CSV file(s) in the channel or paste --output - stdout if the UI supports it.
3. Optional --excel: UTF-8 BOM for Excel on Windows.

bird.json shape (summary)

• location_query: user’s place string.
• region: { code, name, name_cn, kind, parent, match_score } from region-query JSON (first line unless --pick).
• country_code: eBird country (CN, …) — region’s parent if subnational, else region.code.
• observations[]: { time_utc, species, notes, source, image_path?, birdid_stdout? }.

For full fields, run append_sighting.py --help or read scripts/bird_log_schema.md.

Tests

From $SKILL/scripts/:

bash

./run_tests.sh
# or: python3 bird_json_util_test.py && python3 set_region_test.py && …

Related

• Region lookup CLI: superpicky-cli/SKILL.md — ./scripts/run.sh --region-query … --json.