Apology Language Lookup

Bounded offline reference: Popular apology-language frameworks discuss regret, responsibility, restitution, repentance and forgiveness requests. Source: Chapman/Thomaspopular apology framework. Offline bounded framework note, no partner diagnosis, exclusive category, validated instrument or evidence that matching labels guarantees satisfaction. Topic keys: summary, reference, limitations. Not a complete/current reference corpus, individual outcome, legal/design compliance or safety certification.

Description

Popular apology-language frameworks distinguish several ways to discuss repair after harm.

Popular apology-language frameworks distinguish several ways to discuss repair after harm.1

Their labels do not determine whether an apology is sufficient or a partner must forgive. Use this tool to select a short stored reference note.

When to use Apology Language Lookup

Use this tool to select a short stored reference note. Establish the planning scope, matching instrument or reference, observation definitions and currency or time basis.

How to use Apology Language Lookup and understand its results

  1. Establish the planning scope, matching instrument or reference, observation definitions and currency or time basis.
  2. Enter topic, using the field meanings and rules below, then run the tool.
  3. Read result.text. Interpret each field using the units, signs and evidence rules below.
  4. If input validation fails, correct the reported field and run again. Before applying a successful result, check the stated reference scope, units, assumptions and any retained unknown evidence.
Input fieldMeaningValue typeRequirement
topicTopicstringRequired

Choose one of the exact, case-sensitive topic tokens listed below and run the tool. The implementation selects the corresponding stored text from a fixed object and returns it as result.text. Unknown tokens fail rather than fall back. The strings are shipped with the committed implementation: no search, generated forecast, external-corpus retrieval or live update occurs. The table preserves the actual stored wording.

Exact topic tokenActual stored response
summaryPopular apology-language frameworks discuss regret, responsibility, restitution, repentance and forgiveness requests.
referenceChapman/Thomaspopular apology framework.
limitationsOffline bounded framework note, no partner diagnosis, exclusive category, validated instrument or evidence that matching labels guarantees satisfaction.
result.text=storedTopics[exact topic token]

Apply the field units and exact ordering, boundary and evidence rules above.

Output fieldMeaningValue type
resultStructured result containing the calculation or selected reference fields belowobject
result.textStored reference text selected by the exact topic tokenstring
json
{
  "input": {
    "topic": "summary"
  },
  "output": {
    "result": {
      "text": "Popular apology-language frameworks discuss regret, responsibility, restitution, repentance and forgiveness requests."
    }
  }
}

Limitations and assumptions

Coverage is limited to the topic table above. Stored wording may be abbreviated and does not provide a complete external corpus, report, benchmark inventory or updated forecast.

Every listed input requires an explicit value. Unexpected fields, incorrect value types, nonfinite numbers and sparse numeric arrays fail validation; tool-specific bounds and alignment rules apply as described above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful calculation that reports a false comparison or retains unknown evidence.

Alternative or Complementary methods

Use Communication Style Lookup to examine a related aspect: Communication-style labels describe observed or discussed approaches to interaction.

Use Conflict Resolution Style Lookup where its separate inputs and scope apply: Conflict-resolution style records depend on an adopted framework and observation context.

References

  1. Apology Language Lookup — tool.io

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