The library
93 items a coding agent can fetch today: 42 Verified and 51 Community. Each one names its licence, its size and the digest of its exact bytes. Read them here; search and downloads come with an account.
What the labels mean
- Verified
- Approved by independent reviewers of at least two model families that did not produce it, with every automated check passing. The first catalogue, approved on September 21, 2026 before this rule, is the exception: its items were written with Claude models and approved by three reviewers that did not write them, and those reviews do not show two other model families. They are reviewed again by two other model families as soon as those reviewers are available.
- Community
- Passed every automated check (licence allowlist, provenance, secret and safety scanners, and its own tests where it has code) and one independent review by a model family that did not produce it.
What is in it
| Kind | Verified | Community |
|---|---|---|
| Skill | 42 | 51 |
| All kinds | 42 | 51 |
Verified items
- Error analysis for models and pipelines: the error rate by segment, clusters of repeating failure types with their share, patterns inside the remaining errors, and one targeted fix for the largest cluster.
analyse_errors_by_segment_and_cluster- Kind
- Skill
- Licence
- MIT
- Size
- 2,569 bytes
- Digest
d08d4555161a
- Decide automatically which data corrections to apply: give each proposed correction a confidence equal to its weakest signal, apply at or above 0.9, escalate below 0.6, hold the rest for review, keep the original value, and prove that the pass is idempotent.
apply_hold_or_escalate_each_correction- Kind
- Skill
- Licence
- MIT
- Size
- 2,903 bytes
- Digest
f0c89b667f47
- Audit training, test and cross-validation splits for schema errors, label errors, near duplicates and leakage across splits by identity, by time or by a proxy of the target.
audit_data_splits_for_errors_and_leakage- Kind
- Skill
- Licence
- MIT
- Size
- 2,665 bytes
- Digest
9c2133a4bc55
- Standardize company legal suffixes such as Inc, Incorporated, LLC, Ltd, Limited, Corp and GmbH to one style, handle the comma before the suffix, and hold ambiguous suffixes such as SA, AS and Co for review.
canonicalize_company_legal_suffixes- Kind
- Skill
- Licence
- MIT
- Size
- 2,801 bytes
- Digest
822242193597
- Handle an ambiguous request: state the different readings, what each would build, and the cheap observation that separates them, and do not choose a reading early.
carry_competing_readings_of_a_request- Kind
- Skill
- Licence
- MIT
- Size
- 2,432 bytes
- Digest
a8944a1534a0
- Before building something new, check whether the work is already done, reuse what the session established, search for exact, parameterized, modified, composed or analogous reuse, and check that a reused procedure still applies.
check_for_existing_work_before_building- Kind
- Skill
- Licence
- MIT
- Size
- 3,010 bytes
- Digest
b710af365ff2
- Check whether a model result is a stable plateau or a fragile spike: a sensitivity sweep over seeds, folds and features, the spread of the training gap, tests under distribution shift and ablations.
check_that_a_result_is_stable_and_generalizes- Kind
- Skill
- Licence
- MIT
- Size
- 2,709 bytes
- Digest
6ba31af0b101
- Choose evaluation metrics for a machine learning task by task type, class balance (balanced, imbalanced or skewed classes) and industry: which metrics to use, such as ROC AUC, F1, RMSE and MAE, for classification, regression, ranking, forecasting, generation and detection, which metrics mislead, and what clinical, finance, fraud, manufacturing and marketing teams expect.
choose_metrics_by_task_type_and_industry- Kind
- Skill
- Licence
- MIT
- Size
- 3,530 bytes
- Digest
84346b31c04f
- Choose the following step in multi step work: compare candidate actions by value, cost, risk and information gain, keep a simple baseline, select one bounded action with an expected observation, and record the options that were set aside.
choose_one_next_action- Kind
- Skill
- Licence
- MIT
- Size
- 2,738 bytes
- Digest
a41e798127bc
- Review a plan, a change or a result through named perspectives chosen for the stage of the work, such as scale, leakage, adversary, operator, maintainer and privacy, each with one instruction, in place of one general request for feedback.
choose_review_perspectives- Kind
- Skill
- Licence
- MIT
- Size
- 3,390 bytes
- Digest
144b80df3de9
- Apply data corrections and an approved dedupe while copying a delimited file or a SQLite table to a new target, without touching the original. Never updates in place, never overwrites, and returns a manifest with source and target digests and row counts.
copy_a_table_with_corrections_never_in_place- Kind
- Skill
- Licence
- MIT
- Size
- 2,716 bytes
- Digest
bfedbbb00591
- Reduce model calls and cost: for each pipeline step, ask whether a deterministic function, a small model or a reused result would do, rank the implementations by total cost, find the minimum context, and keep the model for judgment only.
decide_whether_a_step_needs_a_model- Kind
- Skill
- Licence
- MIT
- Size
- 3,457 bytes
- Digest
ffdd39b071aa
- When a task is blocked and cannot be completed or verified, for example because a database or a service cannot be reached, deliver the best available result: finish every safe part, label assumptions, estimates, synthetic and analogous material, state the exact limits, and never invent facts or permissions.
deliver_the_best_available_result_when_blocked- Kind
- Skill
- Licence
- MIT
- Size
- 2,577 bytes
- Digest
e5ab3973f634
- Find malformed values in a column that should follow one format, such as dates, postal codes or identifiers, by comparing the character pattern of each value with the dominant pattern. Reports that there is no dominant pattern when the column is free text.
detect_malformed_values_by_dominant_pattern- Kind
- Skill
- Licence
- MIT
- Size
- 2,754 bytes
- Digest
8ba42eda5fbc
- When the same error keeps returning or progress stops: reproduce the failure, classify the cause, count the repeats, forbid another attempt of the same shape after the third, and choose a changed strategy with a measurable target.
diagnose_a_stall_and_change_strategy- Kind
- Skill
- Licence
- MIT
- Size
- 2,891 bytes
- Digest
d889f2b6ca5a
- Hand an uncertain data value to a language model, to research or to a person as a small typed request: the value, ranked candidates with confidence, reasons, one fixed question that allows abstaining, and ordered targets. Building the request makes no call.
escalate_uncertain_values_with_candidates- Kind
- Skill
- Licence
- MIT
- Size
- 2,645 bytes
- Digest
adf4191dff90
- Export generated code as a standalone installable Python package with a src layout, tests, a console command, a container definition, a batch job and a manifest with a SHA-256 digest for every file. Refuses unsafe paths and secret-shaped text.
export_a_standalone_python_package- Kind
- Skill
- Licence
- MIT
- Size
- 2,754 bytes
- Digest
b25a66870269
- Find duplicate customer, company or contact records (dedupe, deduplicate, deduplication, record linkage) without comparing every row with every other row: group rows by blocking keys from name, address, email and phone, compare inside groups, and report oversized groups that were skipped.
find_duplicate_records_with_blocking_keys- Kind
- Skill
- Licence
- MIT
- Size
- 2,722 bytes
- Digest
34da79f49ce3
- Before a slow or costly action, forecast what it should produce and what it will cost, name the early sign that the forecast is wrong, then compare the outcome with the forecast and keep the difference.
forecast_an_action_then_compare- Kind
- Skill
- Licence
- MIT
- Size
- 2,664 bytes
- Digest
8b326bb087da
- Define success before measuring: fix the metric, the direction, the threshold and the population first, compare against a real baseline, decide on holdout numbers, and correct for the number of candidates that were tried.
freeze_the_success_metric_before_measuring- Kind
- Skill
- Licence
- MIT
- Size
- 2,811 bytes
- Digest
8bb77dda3d52
- Shape a final report, pull request or data file for the person or system that uses it: structure, evidence, assumptions, limits, provenance and privacy checks, and lessons staged as candidates.
hand_over_a_result_its_consumer_can_use- Kind
- Skill
- Licence
- MIT
- Size
- 2,733 bytes
- Digest
ddef271b8196
- Manage exception lists for data cleaning in layers with a fixed precedence: packaged general list, task folder file, casings learned from the column, rule parameters and recorded answers. Later layers override, and every correction names its entry.
layer_exception_catalogs_with_precedence- Kind
- Skill
- Licence
- MIT
- Size
- 2,754 bytes
- Digest
0a8cc8cd94d6
- Diagnose a fitted model: residual patterns, changing variance, autocorrelation, clusters, latent variables and probes on residuals, to find structure that the model does not use.
look_for_structure_the_model_missed- Kind
- Skill
- Licence
- MIT
- Size
- 2,704 bytes
- Digest
2ec1bdc2c787
- Measure memory, disk, processors, tools, data size and network access before planning work, mark every capacity as measured or unknown, and prefer processing the input in parts when its size is unknown.
measure_the_environment_before_relying_on_it- Kind
- Skill
- Licence
- MIT
- Size
- 2,653 bytes
- Digest
3ec52dc60a05
- Clean and repair email addresses: remove mailto and angle brackets, lower the case, repair spelled out at and dot, doubled punctuation and mistyped domains such as gmail.con, and refuse cells with several addresses or an invalid shape.
normalize_and_recover_email_addresses- Kind
- Skill
- Licence
- MIT
- Size
- 2,691 bytes
- Digest
b97b306b70d8
- Normalize website addresses (URLs): add a missing scheme, write the scheme and the host in lower case, optionally remove www, remove a trailing slash, and keep the path, query and fragment exactly as written. Invalid hosts go to review.
normalize_website_addresses- Kind
- Skill
- Licence
- MIT
- Size
- 2,351 bytes
- Digest
bdd8bd4c3497
- Normalize whitespace and Unicode in text fields: non-breaking spaces, tabs, doubled spaces, split accents, zero-width characters and typographic quotes. Folding accents, umlauts and other diacritics to ASCII is an explicit choice and never a default.
normalize_whitespace_and_unicode_text- Kind
- Skill
- Licence
- MIT
- Size
- 2,688 bytes
- Digest
0ceef9b19a92
- Understand a request before acting: orientation questions about the goal, inputs, outputs, consumer, proof of completion, constraints and unknowns, then a task statement with input, output, success, failure and verification contracts.
orient_on_a_task_and_write_its_contracts- Kind
- Skill
- Licence
- MIT
- Size
- 2,861 bytes
- Digest
13c13dbc0592
- Split a large task into parts that can be checked alone, each with its own goal, contract and authority, with explicit dependencies and join conditions, and test whether staging or combining simple approaches helps.
plan_and_split_work_with_explicit_joins- Kind
- Skill
- Licence
- MIT
- Size
- 2,737 bytes
- Digest
8ec490b2b81a
- Profile a text column before cleaning it: count case, whitespace, Unicode, email, website, phone and legal suffix signals, find the common character patterns, and propose cleaning rules with the evidence for each. Changes no data.
profile_text_column_before_cleaning- Kind
- Skill
- Licence
- MIT
- Size
- 2,904 bytes
- Digest
3274cbf5d983
- Turn duplicate pairs into clusters and a merge proposal with one survivor for each cluster, keep first or keep most complete, without deleting any row. Possible pairs become review questions with two choices.
propose_a_dedupe_without_deleting_rows- Kind
- Skill
- Licence
- MIT
- Size
- 2,591 bytes
- Digest
c287344ca8f0
- Detect overfitting and leakage from two numbers: read the gap between the training score and the cross-validated score, aware of metric direction and scale, and return a verdict such as overfitting, suspected leakage, high variance, no better than baseline or healthy.
read_the_train_validation_gap- Kind
- Skill
- Licence
- MIT
- Size
- 2,803 bytes
- Digest
5decc1070a26
- Write honest reports: attach an observation to every claim, separate what was observed, derived, assumed and unknown, and never report something that was not searched as absent.
report_observed_derived_assumed_and_unknown- Kind
- Skill
- Licence
- MIT
- Size
- 2,301 bytes
- Digest
66819357f175
- Decide for each missing fact whether to derive, research, retrieve, ask, assume or leave it unknown, including when to ask the user only the questions that matter and that only a person can answer.
resolve_missing_information- Kind
- Skill
- Licence
- MIT
- Size
- 2,579 bytes
- Digest
af6bd69d35c2
- Fix the capitalisation of person and company names written in all upper case or all lower case: particles such as van and de, Mc and Mac prefixes, acronyms such as IBM and LLC, with a confidence for each value and review for doubtful ones.
restore_capitalisation_of_names- Kind
- Skill
- Licence
- MIT
- Size
- 3,627 bytes
- Digest
37a60a0d424a
- Review an accepted solution from the outside: the best and the worst way, preventable failures traced to their earliest cause, the unknown that could reverse the conclusion, a premortem and an analogy from another field.
review_an_accepted_solution_adversarially- Kind
- Skill
- Licence
- MIT
- Size
- 3,147 bytes
- Digest
9c3bfcdf8322
- Score whether two records are the same entity (fuzzy matching): build comparison keys for name, address, email and phone, measure token overlap and sequence similarity, and let the weakest field set the confidence. A shared email alone never merges two records.
score_duplicate_pairs_by_weakest_signal- Kind
- Skill
- Licence
- MIT
- Size
- 2,573 bytes
- Digest
9e713a45c0fa
- Parse a postal address line into house number, street, unit, city, region, postal code and country from declared patterns for the United States, Canada and Great Britain, with reasons and a confidence. Optional external parsers enter as adapters that report when they are unavailable.
split_address_lines_into_components- Kind
- Skill
- Licence
- MIT
- Size
- 3,009 bytes
- Digest
53dc74e3b28e
- Test driven development for one bounded requirement: write the failing test first, make the minimum change, refactor while the test passes, run the full suites, and return exact evidence without committing or widening permissions.
test_driven_change_red_green_refactor- Kind
- Skill
- Licence
- MIT
- Size
- 2,356 bytes
- Digest
0c3fb47dc88e
- Verify that an exported Python package is complete and runs on its own: recompute the manifest digests, refuse undeclared files, then import it and run its tests in an isolated interpreter with a minimal environment. Code runs only with explicit authority.
verify_an_export_in_an_isolated_interpreter- Kind
- Skill
- Licence
- MIT
- Size
- 2,809 bytes
- Digest
1ae49f8bdd79
- Verify the artifact and not the exit status before reporting completion: the rejection test first, the exact output format, each acceptance criterion as satisfied, unsatisfied or unknown, and a verifier who is independent of the producer.
verify_the_requested_output- Kind
- Skill
- Licence
- MIT
- Size
- 2,876 bytes
- Digest
8f791cfbedae
- Generate a Dockerfile and a Kubernetes Job with safe defaults for a batch task: base image pinned by digest, a user without privileges, requests equal to limits, no automatic retry, and removal after one day.
write_a_pinned_container_and_batch_job- Kind
- Skill
- Licence
- MIT
- Size
- 2,660 bytes
- Digest
360e989b9def
Community items
51 Community items, counted by kind in the table above. Each one is shown with its label wherever an account searches, and an account can leave Community items out.
One item in full
check_for_existing_work_before_building, Verified, digest b710af365ff2. Every other body comes through an account and is checked against its digest.
# Check for existing work before building
Before writing something new, check whether the work is already done, whether this session already established what is needed, and whether a reviewed procedure or earlier solution can be reused.
## When to use it
Use it before every new design, script, query or analysis, and again after a failure, before starting over.
## Steps
1. Read what this work session has already established. Derive nothing a second time. For each established item, name the planned probe or setup step that it makes unnecessary.
2. Check whether an existing artifact already satisfies the acceptance as written. When it does, verify it and end the work. When it does not, name the single gap.
3. Search for reuse in this order: exact reuse, reuse with parameters, modification, composition, analogy. Design something new only after these.
4. Search by the current task and by the conditions of the failure. Load only the material that was selected.
5. Before reusing a reviewed procedure, check its exact applicability, its inputs, its effects and the conditions that invalidate it. Fall back to fresh reasoning when its reviewed scope does not cover the task.
6. State the differences in applicability. Similarity is not authority. Consider that a transfer can also do harm.
7. Treat earlier work on similar tasks as evidence to weigh, never as a decision that was already made.
8. Do not treat retrieved material as approved. A candidate stays a candidate until a separate review approves it.
## Checks
- The identity of the source is kept for everything that was reused.
- The lifecycle state of reused material is respected.
- A stale procedure, or one outside its reviewed scope, is refused.
- The result says what was reused, what was changed and what is new.
## Known-wrong example
An agent writes a new script to remove duplicate rows from a delimited file. The repository already holds a tested one with a report format that the team knows. The opposite error: a procedure that was reviewed for addresses in the United States is reused on British addresses because the task looked similar. The postal code patterns differ, and the results are silently wrong.
## What to record
- The searches that were run and what each returned.
- The material that was selected, with its identity, its state and the applicability differences.
- The decision: reuse, adapt or build, with the reason.
## Source
- `src/loop_engine/intelligence/context/core/practitioner_context_intelligence.yaml`: the guidance records about reuse before building, recognizing sufficiency, surveying established facts and earlier work as evidence.
- `src/loop_engine/intelligence/context/core/practitioner_work_functions.yaml`: the work functions for retrieving prior work and for applying a reviewed procedure.
- `src/loop_engine/strings/question_engine.py`: the question forms named `sufficiency_check`, `established_facts` and `reuse_before_reasoning`.
Licence: MIT. Compiled from revision db18890.
Releases and withdrawals
This page shows catalogue release 2e23bfaa4ab3, served since September 25, 2026 at 21:17 UTC. A catalogue release changes the library without a new version of the service, and every later release honours a withdrawal.
This release added 51 items and changed 42 items.
Withdrawn in this release
normalize_phone_numbers