Parsing Lab Values

What it does

When your agent uses it

• The user needs to interpret lab results
• Compute abnormal flags
• Parse reference ranges like 135-145
• Honor an originating-lab flag (H/L/critical)

Example prompts

• “/parsing-lab-values”

Requirements

• Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Get value + range + (optional) lab flag from extracted lab entities. The
2. 2Parse the reference range with parse_reference_range. It handles closed
3. 3Derive the flag with derive_abnormal_flag(value, range, explicit_flag=).
4. 4Handle "unknown" explicitly. Non-numeric values, empty/unparseable
5. 5Attach the advisory. Surface LAB_FLAG_ADVISORY wherever derived flags

What it can do on your machine

Read from SKILL.md and the folder at commit 34d7b8c. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • loinc.org
  • ucum.org
  • terminology.hl7.org
  • hl7.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Parsing Lab Values loads about 1.6k tokens when it runs. Until then it costs about 159 tokens; SKILL.md has 588 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~159

When it runs · the whole SKILL.md, loaded when a task matches

~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from maziyarpanahi/openmed at commit 34d7b8c, republished under its Apache-2.0 licence (© maziyarpanahi). 588 words, ~1,636 tokens.

name

parsing-lab-values

description

Parse laboratory values and reference ranges from clinical text and flag results as low, normal, high, or critical with OpenMed. Use when the user needs to interpret lab results, compute abnormal flags, parse reference ranges like "135-145" or "<5", honor an originating-lab flag (H/L/critical), or turn extracted lab entities into structured high/low/critical signals. Covers openmed.clinical.parse_reference_range, derive_abnormal_flag, ReferenceRange, and AbnormalFlag, with UCUM/LOINC framing. Unit-agnostic — it does not convert units. Pairs after extracting-clinical-entities (lab entities from analyze_text).

license

Apache-2.0

metadata.project

OpenMed

metadata.category

clinical-nlp

metadata.pairs

after

metadata.version

1.0

from openmed.clinical import (
    parse_reference_range, derive_abnormal_flag, LAB_FLAG_ADVISORY,
)

# Closed range
rng = parse_reference_range("135-145")
# -> {"low": 135.0, "high": 145.0, "low_inclusive": True, "high_inclusive": True}

derive_abnormal_flag(132, rng)            # "low"
derive_abnormal_flag(140, "135-145")      # "normal"  (raw range string accepted)
derive_abnormal_flag(150, "135 to 145")   # "high"

# One-sided bounds
derive_abnormal_flag(7, parse_reference_range("<5"))    # "high" (above the cap)
derive_abnormal_flag(3, parse_reference_range(">=10"))  # "low"

# Honor the lab's own explicit flag (takes precedence over derived comparison)
derive_abnormal_flag(132, "135-145", explicit_flag="C")   # "critical"
derive_abnormal_flag(132, "135-145", explicit_flag="HH")  # "critical"

# Unparseable / non-numeric inputs fail safe rather than guessing
derive_abnormal_flag("pending", "135-145")  # "unknown"
derive_abnormal_flag(132, "see report")     # "unknown"

print(LAB_FLAG_ADVISORY)  # surface this disclaimer with derived flags

© maziyarpanahi, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/parsing-lab-values of maziyarpanahi/openmed.

Open the folder on GitHubat commit 34d7b8c