CounterScript - Drug Price Benchmarks

Quality 77 / 100good

1 tools, about 918 tokens to load them all · tool set 96b3c6634d35 · tools last changed 2026-10-12 · checked 2026-10-19 10:52 UTC

Tool changes

• 2026-10-12drug_pricechangeddescription
  before

  Looks up what US pharmacies actually pay to acquire a drug (the CMS NADAC benchmark, per unit, with its date), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where they apply. The input is a drug name with optional strength and form. result_type is one of three values. match: one drug, with prices, provenance and honesty notes; a brand-name drug with no generic alternatives listed also carries generic_equivalence, a dated statement of what the FDA Orange Book shows for it. A brand-name match can also carry cms_generic_price, CMS's NADAC figure for the corresponding generic drug, with its effective date, a fair cash estimate where a fill quantity applies, and the generic's name when exactly one generic in the index has that price, strength and ingredient. A biologic that the FDA Purple Book lists biosimilars to also carries biosimilars (each with proprietary and proper names, interchangeable, marketing_status, file_month, and a NADAC price where one is indexed) and biosimilars_statement; a biosimilar carries reference_product, with the same kinds of fields and a statement. candidates: the query fits several drugs. Up to 12 are listed (generic drugs first, then alphabetical), each with its description and price hint. candidates_total gives how many drugs matched; when that is more than 12, message says the list was cut, and adding a strength or form narrows it. A query equal to one candidate's description returns that drug as a match. no_match: the index has no drug matching the query, with close drug names in did_you_mean where any exist; this does not mean the drug lacks a fair price, since NADAC covers only drugs with enough pharmacy survey data. Every result also carries freshness, one entry per source (nadac, orangebook, mfp, purplebook) giving as_of, the publisher's date on the file in use (for purplebook, which FDA dates by month, the first day of that month); checked, the date of our newest successful fetch of that source; expected, the publishing cadence (weekly, monthly or irregular); and stale, which is true when the NADAC file is more than 10 days old, the Orange Book file more than 45 days old or the month of the Purple Book file ended more than 60 days ago, or when our newest attempt to fetch that source failed (last_attempt_failed then gives that attempt's date, and the file in use is the newest good one we hold), and then statement says so in plain words. For mfp, whose updates are irregular, stale is true only after a failed fetch. A source we have not fetched yet has no as_of or checked.

  after · 83% of words in common

  Looks up what US pharmacies actually pay to acquire a drug (the CMS NADAC benchmark, per unit, with its date), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where they apply. The input is a drug name with optional strength and form. result_type is one of three values. match: one drug, with prices, provenance and honesty notes; a brand-name drug with no generic alternatives listed also carries generic_equivalence, a dated statement of what the FDA Orange Book shows for it. A brand-name match can also carry cms_generic_price, CMS's NADAC figure for the corresponding generic drug, with its effective date, a fair cash estimate where a fill quantity applies, and the generic's name when exactly one generic in the index has that price, strength and ingredient. A biologic that the FDA Purple Book lists biosimilars to also carries biosimilars (each with proprietary and proper names, interchangeable, marketing_status, file_month, and a NADAC price where one is indexed) and biosimilars_statement; a biosimilar carries reference_product, with the same kinds of fields and a statement. candidates: the query fits several drugs. Up to 12 are listed (generic drugs first, then alphabetical), each with its description and price hint. candidates_total gives how many drugs matched; when that is more than 12, message says the list was cut, and adding a strength or form narrows it. A query equal to one candidate's description returns that drug as a match. no_match: the index has no drug matching the query; this does not mean the drug lacks a fair price, since NADAC covers only drugs with enough pharmacy survey data. did_you_mean, where present, lists drug names to search next, and did_you_mean_basis gives the reason: spelling (names spelled like the query; for a trade name that is its only active ingredient plus more words, such as theophylline-sr, that ingredient) or same_ingredient (the index has no drug under the ingredient name in the query, and the names are priced brands whose only active ingredient in the FDA Orange Book is that ingredient; store brands of the ingredient may still be priced under their own names). Names that differ from the query by a letter or two appear only when the query is not recognized in the loaded FDA Orange Book or Purple Book names. These catalogs omit some drug names; a spelling hint is a search aid, not an equivalent medicine. Every result also carries freshness, one entry per source (nadac, orangebook, mfp, purplebook) giving as_of, the publisher's date on the file in use (for purplebook, which FDA dates by month, the first day of that month); checked, the date of our newest successful fetch of that source; expected, the publishing cadence (weekly, monthly or irregular); and stale, which is true when the NADAC file is more than 10 days old, the Orange Book file more than 45 days old or the month of the Purple Book file ended more than 60 days ago, or when our newest attempt to fetch that source failed (last_attempt_failed then gives that attempt's date, and the file in use is the newest good one we hold), and then statement says so in plain words. For mfp, whose updates are irregular, stale is true only after a failed fetch. A source we have not fetched yet has no as_of or checked.

• 2026-10-09drug_pricechangeddescription
  before

  Looks up what US pharmacies actually pay to acquire a drug (the CMS NADAC benchmark, per unit, with its date), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where they apply. The input is a drug name with optional strength and form. result_type is one of three values. match: one drug, with prices, provenance and honesty notes; a brand-name drug with no generic alternatives listed also carries generic_equivalence, a dated statement of what the FDA Orange Book shows for it. A brand-name match can also carry cms_generic_price, CMS's NADAC figure for the corresponding generic drug, with its effective date, a fair cash estimate where a fill quantity applies, and the generic's name when exactly one generic in the index has that price, strength and ingredient. A biologic that the FDA Purple Book lists biosimilars to also carries biosimilars (each with proprietary and proper names, interchangeable, marketing_status, file_month, and a NADAC price where one is indexed) and biosimilars_statement; a biosimilar carries reference_product, with the same kinds of fields and a statement. candidates: the query fits several drugs. Up to 12 are listed (generic drugs first, then alphabetical), each with its description and price hint. candidates_total gives how many drugs matched; when that is more than 12, message says the list was cut, and adding a strength or form narrows it. A query equal to one candidate's description returns that drug as a match. no_match: the index has no drug matching the query, with close drug names in did_you_mean where any exist; this does not mean the drug lacks a fair price, since NADAC covers only drugs with enough pharmacy survey data. Every result also carries freshness, one entry per source (nadac, orangebook, mfp, purplebook) giving as_of, the publisher's date on the file in use (for purplebook, which FDA dates by month, the first day of that month); checked, the date of our newest successful fetch of that source; expected, the publishing cadence (weekly, monthly or irregular); and stale, which is true when the NADAC file is more than 10 days old, the Orange Book file more than 45 days old or the month of the Purple Book file ended more than 60 days ago, and then statement says so in plain words. stale is false for mfp, whose updates are irregular. A source we have not fetched yet has no as_of or checked.

  after · 97% of words in common

  Looks up what US pharmacies actually pay to acquire a drug (the CMS NADAC benchmark, per unit, with its date), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where they apply. The input is a drug name with optional strength and form. result_type is one of three values. match: one drug, with prices, provenance and honesty notes; a brand-name drug with no generic alternatives listed also carries generic_equivalence, a dated statement of what the FDA Orange Book shows for it. A brand-name match can also carry cms_generic_price, CMS's NADAC figure for the corresponding generic drug, with its effective date, a fair cash estimate where a fill quantity applies, and the generic's name when exactly one generic in the index has that price, strength and ingredient. A biologic that the FDA Purple Book lists biosimilars to also carries biosimilars (each with proprietary and proper names, interchangeable, marketing_status, file_month, and a NADAC price where one is indexed) and biosimilars_statement; a biosimilar carries reference_product, with the same kinds of fields and a statement. candidates: the query fits several drugs. Up to 12 are listed (generic drugs first, then alphabetical), each with its description and price hint. candidates_total gives how many drugs matched; when that is more than 12, message says the list was cut, and adding a strength or form narrows it. A query equal to one candidate's description returns that drug as a match. no_match: the index has no drug matching the query, with close drug names in did_you_mean where any exist; this does not mean the drug lacks a fair price, since NADAC covers only drugs with enough pharmacy survey data. Every result also carries freshness, one entry per source (nadac, orangebook, mfp, purplebook) giving as_of, the publisher's date on the file in use (for purplebook, which FDA dates by month, the first day of that month); checked, the date of our newest successful fetch of that source; expected, the publishing cadence (weekly, monthly or irregular); and stale, which is true when the NADAC file is more than 10 days old, the Orange Book file more than 45 days old or the month of the Purple Book file ended more than 60 days ago, or when our newest attempt to fetch that source failed (last_attempt_failed then gives that attempt's date, and the file in use is the newest good one we hold), and then statement says so in plain words. For mfp, whose updates are irregular, stale is true only after a failed fetch. A source we have not fetched yet has no as_of or checked.

• 2026-09-29drug_pricechangeddescription
  before

  Looks up what US pharmacies actually pay to acquire a drug (the CMS NADAC benchmark, per unit, with its date), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where they apply. The input is a drug name with optional strength and form. result_type is one of three values. match: one drug, with prices, provenance and honesty notes; a brand-name drug with no generic alternatives listed also carries generic_equivalence, a dated statement of what the FDA Orange Book shows for it. candidates: the query fits several drugs. Up to 12 are listed (generic drugs first, then alphabetical), each with its description and price hint. candidates_total gives how many drugs matched; when that is more than 12, message says the list was cut, and adding a strength or form narrows it. A query equal to one candidate's description returns that drug as a match. no_match: the index has no drug matching the query, with close drug names in did_you_mean where any exist; this does not mean the drug lacks a fair price, since NADAC covers only drugs with enough pharmacy survey data.

  after · 63% of words in common

  Looks up what US pharmacies actually pay to acquire a drug (the CMS NADAC benchmark, per unit, with its date), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where they apply. The input is a drug name with optional strength and form. result_type is one of three values. match: one drug, with prices, provenance and honesty notes; a brand-name drug with no generic alternatives listed also carries generic_equivalence, a dated statement of what the FDA Orange Book shows for it. A brand-name match can also carry cms_generic_price, CMS's NADAC figure for the corresponding generic drug, with its effective date, a fair cash estimate where a fill quantity applies, and the generic's name when exactly one generic in the index has that price, strength and ingredient. A biologic that the FDA Purple Book lists biosimilars to also carries biosimilars (each with proprietary and proper names, interchangeable, marketing_status, file_month, and a NADAC price where one is indexed) and biosimilars_statement; a biosimilar carries reference_product, with the same kinds of fields and a statement. candidates: the query fits several drugs. Up to 12 are listed (generic drugs first, then alphabetical), each with its description and price hint. candidates_total gives how many drugs matched; when that is more than 12, message says the list was cut, and adding a strength or form narrows it. A query equal to one candidate's description returns that drug as a match. no_match: the index has no drug matching the query, with close drug names in did_you_mean where any exist; this does not mean the drug lacks a fair price, since NADAC covers only drugs with enough pharmacy survey data. Every result also carries freshness, one entry per source (nadac, orangebook, mfp, purplebook) giving as_of, the publisher's date on the file in use (for purplebook, which FDA dates by month, the first day of that month); checked, the date of our newest successful fetch of that source; expected, the publishing cadence (weekly, monthly or irregular); and stale, which is true when the NADAC file is more than 10 days old, the Orange Book file more than 45 days old or the month of the Purple Book file ended more than 60 days ago, and then statement says so in plain words. stale is false for mfp, whose updates are irregular. A source we have not fetched yet has no as_of or checked.

• 2026-09-28drug_pricechangedtitle, descriptionmeaning changed
  before

  Look up what US pharmacies actually pay to acquire a drug (CMS NADAC benchmark), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where applicable. Returns match, candidates (disambiguate and call again), or no_match.

  after · 24% of words in common

  Looks up what US pharmacies actually pay to acquire a drug (the CMS NADAC benchmark, per unit, with its date), a fair cash-price estimate range, FDA generic equivalents, and Medicare negotiated prices where they apply. The input is a drug name with optional strength and form. result_type is one of three values. match: one drug, with prices, provenance and honesty notes; a brand-name drug with no generic alternatives listed also carries generic_equivalence, a dated statement of what the FDA Orange Book shows for it. candidates: the query fits several drugs. Up to 12 are listed (generic drugs first, then alphabetical), each with its description and price hint. candidates_total gives how many drugs matched; when that is more than 12, message says the list was cut, and adding a strength or form narrows it. A query equal to one candidate's description returns that drug as a match. no_match: the index has no drug matching the query, with close drug names in did_you_mean where any exist; this does not mean the drug lacks a fair price, since NADAC covers only drugs with enough pharmacy survey data.

• 2026-09-27drug_pricechangedannotations

Full history: list_changes · trend: quality JSON.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.