6.0 KiB
title, task, lineage_type, upstream_source, upstream_sha, imported_at, prompt_class, upstream_changes, author, validated
| title | task | lineage_type | upstream_source | upstream_sha | imported_at | prompt_class | upstream_changes | author | validated |
|---|---|---|---|---|---|---|---|---|---|
| Code Patterns Reference | import | https://github.com/mims-harvard/ToolUniverse/blob/3038dcbe/skills/devtu-code-optimization/references/code-patterns.md | 3038dcbe | 2026-06-30 | prompt | accepted | upstream | false |
Code Patterns Reference
Reusable implementation patterns for ToolUniverse tool development.
Schema Patterns
return_schema with oneOf (required)
{
"return_schema": {
"oneOf": [
{
"type": "object",
"properties": {
"data": {"type": "object"},
"metadata": {"type": "object"}
}
},
{
"type": "object",
"properties": {
"error": {"type": "string"}
}
}
]
}
}
Nullable fields
{"type": ["array", "null"]}
{"type": ["string", "null"]}
API Call Patterns
Client-Side Filter (when API ignores params)
results = api_call(base_params_only)
if interaction_types:
results = [r for r in results if r.get("type") in interaction_types]
if sources:
results = [r for r in results if r.get("source") in sources]
Fallback Lookup
precise = api_call(geneSymbol=gene_symbol)
if not precise:
precise = api_call(name=gene_symbol)
Client-Side Pagination (when API ignores size/page)
all_items = api_call()
start = page * size
return all_items[start:start + size]
PostgREST Join
url = f"{base}/recommendation?select=*,drug(name)&genesymbol={_postgrest_eq(gene)}"
Output Patterns
Normalization Disclosure
_norm_parts = []
if original != normalized:
_norm_parts.append(f"'{original}' → '{normalized}' (reason)")
if _norm_parts:
result["normalization_note"] = "Auto-normalized: " + "; ".join(_norm_parts)
Truncation at Top Level
response = {"status": "success", "data": data[:limit]}
if len(data) > limit:
response["truncated"] = True
response["truncation_note"] = (
f"Returning {limit} of {len(data)}. "
f"Pass max_results={len(data)} for full data."
)
No-Data vs Bad-Query
if count == 0 and query:
result["hint"] = f"No results for '{query}'. Try a broader term or check spelling."
elif count == 0:
result["hint"] = "No data available for this entity."
Hosted Model-API Tools (NVIDIA NIM-style)
Async poll host = the invocation host
Poll a 202 job-status on the SAME gateway you POSTed to. NVCF biology NIMs invoke
and poll on health.api.nvidia.com; integrate.api.nvidia.com serves only the
OpenAI-compatible LLM endpoints and has no /v1/status route.
host = urlparse(self.base_url).netloc # e.g. health.api.nvidia.com
poll_url = f"https://{host}/v1/status/{req_id}"
Route-existence probe (find/verify hosted endpoints)
Plain-text 404 page not found = route does NOT exist; a structured
{"status":404,...} (or 400/422/200) = route exists. Use the live API to confirm a
model is hosted and to find the right slug before wrapping it.
Unwrap JSON envelopes around the "raw" payload
Some endpoints return {"pdbs": ["...ATOM..."]} even when response_type is pdb.
Unwrap to the inner value so the field matches the schema (real PDB, not a JSON blob).
HTTP 200 with an inner failure
A 200 can carry {"status": "failed", ...} (e.g. DiffDock with an unreadable
ligand). Surface it as an error — but only on explicit failed/error/errored; an
inner status:"success" must stay a success (don't over-match).
404 "not found for account" ≠ wrong path
A gated/unprovisioned model returns a 404 whose body says "Not found for account". Report "model not available for your account" rather than "endpoint not found".
Retry a longer poll window before declaring "broken"
A heavy async job can return 504 / nvcf-status: errored simply because
NVCF-POLL-SECONDS was shorter than its runtime. Only a persistent 400
DEGRADED/error across retries is a real outage. 5xx bodies are often empty —
surface nvcf-status / nvcf-reqid from the headers instead.
Model-variant selection via templated endpoint
Expose multiple hosted sizes through one tool: a {placeholder} in the endpoint +
fields.path_params default, filled from the request arg (sanitized slug) and
stripped from the request body.
# endpoint "arc/{model}/generate", path_params {"model": "evo2-40b"}
value = args.get(key) or default
if not re.fullmatch(r"[A-Za-z0-9._-]+", str(value)): # no path injection
value = default
endpoint = endpoint.replace("{" + key + "}", value)
R-subprocess Tools
Run a script file, not Rscript -e <string>
Rscript -e collapses one backslash level before R parses it, so a regex literal
like sub("\\..*", ...) becomes sub("\..*", ...) and R aborts with
'\.' is an unrecognized escape. Write the script to a temp .R file and run
Rscript <file> (parsed verbatim); always remove the temp file, incl. on timeout.
tmp = tempfile.NamedTemporaryFile(mode="w", suffix=".R", delete=False)
try:
tmp.write(r_script); tmp.close()
return subprocess.run(["Rscript", tmp.name], capture_output=True, text=True, timeout=t)
finally:
try: os.unlink(tmp.name)
except OSError: pass
try/except Indentation (Critical)
# CORRECT
try:
resp = requests.get(url)
data = resp.json()
except Exception as e:
return {"status": "error", "error": str(e)}
# WRONG — SyntaxError
try:
resp = requests.get(url)
if resp.ok: # ← same indent as try: → OUTSIDE try block
data = resp.json()
except Exception: # ← Python: "try without except"
pass
Every try: must have except: at the exact same indentation level.
Multi-Word Search Hint
if result["count"] == 0 and name_q and " " in str(name_q):
first_word = str(name_q).split()[0]
result["multi_word_hint"] = (
f"Search may not match multi-word phrases like '{name_q}'. "
f"Try a single keyword: name='{first_word}'."
)