Usage examples¶
The five cases below follow people using Legible to preserve contributions and decide how to continue their work. They are fictional stories, with people, situations and results invented to explain how it works. They describe neither actual deployments nor measured benefits.
Initial description. This is a brief, initial description of possible uses. Experience with the protocol, real cases that may be documented and improvements to tools and infrastructure may clarify, extend or correct the paths presented. These examples remain fictional; they are not accounts of demonstrated results.
The cases use formal records: Appoint to declare a formulation, Trace to declare a relationship with other work and Nod to recognize a consequence received. The same people could begin with private, unsigned drafts. The draft examples show that path. The specification defines formats and requirements.
The economic coordination guide explains access to results, percentage recognition chosen after the consequence and infrastructure continuity.
Deliver a part and decide whether to continue¶
Ana runs a corporate information-security training service. At the companies she serves, she encounters a difficulty: the contract records the purchase of training, but what changed afterward is not always clear. The client knows they had access to the classes; deciding whether another stage is worthwhile requires reconstructing what the team managed to apply.
In an Appoint, Ana declares that problem. In another, she restates the problem and proposes an experiment: deliver the work in small parts, present the evidence for each stage and wait for the client to declare the consequence they received. After each delivery, she decides whether to offer the next part. In the origin Traces, she identifies the guides and work on which she based this formulation.
Ana knows forms of remuneration that depend on results. She is not suggesting that Legible invented that possibility. She wants to try a relationship in which the client's recognition, given after receiving part of the work, helps inform continuity. The protocol allows that recognition and its references to be recorded; it defines neither a price list nor a payment order.
Bruno, who is responsible for the area at the client company, reads the proposal. His objection is practical: in an earlier experience, measuring and discussing results consumed much of the effort he hoped to save. Ana proposes starting with a small pilot. They clarify what will be delivered, which evidence they can examine and who can access it. Bruno is authorized to report, on behalf of the company, the consequences received in this pilot.
Ana prepares the training design and applies it with a small team. In this story, she decides to conduct that first stage without charging in advance. This takes time for discussion, preparation and execution. She does not know whether she will receive recognition or money, and the record does not eliminate that risk.
After delivery, Ana waits for Bruno's Nod. He examines the pilot and declares that the design enabled the team to identify situations they had previously failed to recognize. He signs a reputational Nod referencing Ana's contribution and the test evidence. There is no monetary transfer in this first cycle.
Ana reads the declaration. The client described a concrete consequence, and she considers it worthwhile to invest in another stage. She decides to offer application of the training in a real project. Bruno agrees to participate. At the end of that stage, he recognizes the observed application and chooses to transfer an amount in recognition. The transfer takes place through the external means chosen for it. The new monetary Nod states the amount Bruno declares already transferred and identifies the contribution in that second stage.
The two declarations give Ana different information: the first describes a consequence without payment; the second describes another consequence and a transfer. She considers what she received, the effort required and the work still ahead before deciding whether to offer a third cycle. Issuing a Nod does not automatically contract that new stage.
The circuit also allows another outcome. If the first Nod did not arrive, Ana could talk to Bruno, continue anyway or decide not to offer further work. The protocol would impose no automatic transition. Ana would know only that she had not received the recognition she expected; the lack of a visible record would not let her conclude that no benefit occurred or that Bruno never recorded anything privately.
Delivering in parts limits the work Ana chooses to offer before assessing the return. This does not guarantee that the service can sustain itself. She has already spent resources on the first cycle and needs to consider the risk of continuing without receiving money. Separate agreements can exist; this experiment examines the possibility of delivering, waiting for recognition and choosing the next step. Any commitments actually undertaken remain relevant to that choice.
If Bruno authorizes sharing the Nods, another provider can examine what he recognized, under which circumstances and with what evidence. That can inform a new working relationship. The reader still needs to assess the content: three Nods are not a reliability score, and a signature does not prove that the declared consequences happened.
Ana wants to observe two things: whether accessible history makes starting a relationship easier to decide, and whether recognition by stage helps guide continuation. To assess the experience, she also needs to count time spent preparing records, examining evidence and discussing recognition. The story shows the circuit; it does not establish that it is cheaper.
R&D: preserve an observation before funding the test¶
An equipment company maintains a research and development laboratory with ten researchers. The team already writes reports, records experiments and conducts performance reviews. Even so, when returning to older projects, it encounters a problem: people know a route was abandoned, but cannot always establish who identified the difficulty, what analysis they relied on or why that conclusion seemed sufficient at the time.
Helena, the R&D director, proposes an internal pilot. In an Appoint, she describes this loss of memory. In another, she restates the problem and proposes preserving observations, formulations and dependencies before deciding which tests will receive resources. In the Traces she identifies the materials used to design the pilot. Investment decisions remain with the people authorized by the company.
Rafael works on a prototype with intermittent failures. Before a new experiment has been approved, he records an Appoint: “In the available tests, the prototype fails above 40 °C. The routine tests, conducted at 22 °C, do not reproduce that condition.” He references the reports and describes which results he examined. The observation is preserved even if the additional test is not approved.
Marina reads the record and relates it to a problem in her materials analysis. In her own Appoint, she formulates the hypothesis that temperature explains a polymer behavior she has not yet managed to reproduce. She declares a Trace between her analysis and Rafael's observation, explaining how she relied on it. The record attributes that relationship to Marina; it does not present it as a conclusion Rafael signed.
Helena finds the two works while examining proposals for the next cycle. In her CH, a private document that guides her reading, she had written that she was looking for signs of failures not covered by routine tests and questions that could be investigated with the available resources. This context guides her reading. She can ask an AI authorized to process the internal materials for help, but remains responsible for assessing the hypothesis and deciding what to take to the team.
Helena approves a thermal-chamber test. In the fictional scenario, the test reproduces the failure and supplies information for revising the prototype's material. Authorized to report consequences received by the company, Helena issues two operational reputational Nods: one references Rafael's observation; the other, Marina's analysis. In each declaration she explains what that contribution helped them understand and references the relevant evidence. Neither record executes a payment or determines a promotion.
Months later, Rafael leaves the company and Marina changes projects. Diego takes over the investigation and finds the files the company preserved in the internal space: the initial observation, hypothesis, declared dependency, test reports and recognitions. He can reconstruct part of the path without relying only on the memory of those who participated.
Diego can examine the evidence and reach another conclusion. If new tests indicate another cause, he preserves his analysis and declares which works he relied on or which conclusions he disputes. Earlier declarations remain attributed to their declarants; Helena's Nod does not make the initial explanation a definitive truth.
Helena wants to assess whether the team can preserve and reconsider contributions before selecting them for execution. The records help Diego only because someone maintained the files, references and access to the material. The protocol does not guarantee that continuity alone. The relevant comparison is with the reports and experiment records the team could already maintain, including the additional effort required by the pilot.
The pilot concerns research memory. If the company wants to use these data for performance reviews too, it needs to define and communicate that other purpose, its criteria and applicable conditions. A contribution may matter even without a visible Nod; the collection is not a complete register of the researchers' merit.
Meetings: arrive with the path already documented¶
A software company has three teams distributed across two time zones. It uses Git, issues, documents and chat. In weekly meetings, however, much of the time goes to questions about the path of the work: why a solution was proposed, which information changed a priority and what led to abandoning an alternative. The answers are scattered and do not always identify who adopted each analysis.
Paula, the engineering director, proposes a pilot with one team. She records the problem in an Appoint and, in another, proposes preserving formulations and dependencies at moments when a question or decision changes. The hypothesis is that reading these records before a meeting will reduce the time needed to reconstruct context. The team does not need to turn every progress update into a Legible record.
Tiago examines the new-user onboarding process. In this case's fictional data, he identifies a concentration of dropouts at email confirmation. In an Appoint, he formulates the question: “We are trying to simplify registration, but the largest observed dropout comes afterward. What prevents email confirmation?” He references the period analyzed, the funnel and support accounts, kept in authorized internal storage.
Lívia reads the observation and prepares a proposal to revise confirmation. She preserves her formulation in an Appoint and declares its dependency on Tiago's work. The proposal explains what she suggests changing and what still needs testing. Another reader can therefore distinguish the problem formulated by Tiago from the solution proposed by Lívia.
Before the next meeting, participants read these materials and note their questions. The discussion begins with what still needs a decision: is this test worth prioritizing now? Authorized people decide resources, deadlines and execution through company processes. The decision and its rationale can be referenced afterward; the Appoint assigns no task to anyone.
After the meeting, Paula reports, on behalf of the company and with authorization to do so, a consequence already received: Tiago's observation helped identify the problem the team needed to discuss; Lívia's proposal helped delimit a testable alternative. She issues a reputational Nod for each contribution. These recognitions concern preparation of the decision, not a product improvement that has yet to be observed.
After testing the new flow, the results may support another declaration, with its own content and references. This distinguishes “this analysis helped us decide” from “this change produced the result we observed”. The Nods do not replace minutes or other records the company needs to maintain.
When Caio joins the team, he finds the problem formulation, proposal, declared dependency, decision and available results. He can understand why the test was chosen without calling another meeting just to hear the whole story. If the bottleneck has changed, he can formulate a new question; preserving an earlier decision does not require continuing to follow it.
When assessing the pilot, Paula compares meeting time with the earlier period and examines the experience of another team that did not change its process. She also counts time spent writing, finding and reading records, questions that persisted and information that was missing. Differences in projects, participants and workload may affect the comparison. A shorter meeting alone demonstrates neither saved effort nor that Legible caused the change.
Paula is looking for a concrete outcome: can people arrive at the discussion knowing what was formulated, what it relied on and what still needs deciding? The test may show advantages, excessive effort or no gain over well-maintained documentation. All three outcomes help decide whether to continue.
A collaborative business: contributions before the client¶
A group wants to develop a service to improve support at small companies. Joana preserves an Appoint about a problem she observed: teams record tickets but lose the reasons certain cases require rework. André formulates a way to relate tickets and corrections. Luiza proposes starting by reviewing a small sample, because integrating every system at once may cost more than the service can offer.
The three works stay in the group's authorized repository. Each participant adopts their formulation and can keep investigating other possibilities. At that moment there is no common client or decision to execute everything. Other people add sales proposals, questions and objections.
Later, Miguel finds an interested company. He will lead delivery and undertake the commitments of his service. With the relevant authorization, he describes the demand in an Appoint: the client wants to understand rework causes without moving support data outside the authorized environment and prefers to begin with a small stage.
Joana reads the demand and formulates a solution proposal. In that new Appoint's origin Traces, she declares how she used the initial problem, André's proposal and the condition Luiza suggested. Someone else presents an alternative based on broader integration. The proposals can coexist.
Miguel asks an AI authorized to read the materials for help. It compares the two alternatives with the client's conditions, identifies documents examined and raises a question: does the available sample allow investigation of the relevant cases? Participants discuss it. Miguel chooses Joana's proposal for the initial stage, considering the available evidence and the commitment he can undertake. The AI neither creates that commitment nor invalidates the other proposal.
Before the work, Miguel and Joana agree on how to examine the service results. They define documents, calculation criteria and who will have access, respecting the client's authorized boundaries. That agreement fixes no recognition percentage for Joana or every antecedent of the solution. The terms of the client service are handled separately.
In the fictional scenario, the stage is executed. The analysis separates rework causes that had been mixed together, and Miguel delivers the service with less manual reconstruction than expected. After learning the results and examining the documents, he chooses to propose recognition to Joana corresponding to 3% of that service's calculated result, under the specific terms he presents. The percentage was chosen after the consequence; it was not remuneration previously promised for that contribution.
Miguel prepares a non-monetary Nod referencing Joana's solution Appoint by
its record identifier (RecordID). In the statement, he explains the consequence, the 3% proposal
and its base. agreement-hash-reference identifies the exact terms detailing
calculation, amounts, data access and proposal conditions. The Nod records the
proposed arrangement; it does not declare money already transferred.
Joana reads the terms and available documents and accepts through the procedure
chosen by the parties. She also issues an agreement-decision .response
with signal accepted about that Nod. Joana's key declaration and the external
acts of the relationship must remain distinguishable. If terms change, the
earlier acceptance does not silently apply to the new proposal.
Miguel and Joana authorize disclosure of the declaration and percentage while amounts and documents remain restricted to authorized people. A reader of the public Nod can learn what Miguel recognized and proposed. Without contract and data access, they cannot check the entire calculation or conclude that a transfer happened.
If a monetary Nod is later issued, it will state the amount declared already transferred and the currency, with the disclosure chosen for that new record. The proposal and transfer are not two payments. The Traces do not automatically distribute the 3% among earlier authors either. Joana can examine consequences she received from André's, Luiza's and other sources' contributions and make her own recognitions.
In another opportunity, a participant can examine accessible history before offering work to Miguel. They will find situated declarations, not a guarantee of receiving the same terms. The group can observe whether reading helped consider previously overlooked contributions and whether returns let authors continue participating. Those are different questions from merely managing to keep files in a repository.
A shared infrastructure and its independent uses¶
Teresa participates in a community laboratory maintaining equipment, a testing workbench and a materials dataset. The laboratory existed before its users learned about Legible. Maintenance depends on work, space, calibration, parts replacement and result storage. Usage fees and partner support cover some of those expenses.
Beatriz develops a component for a client. She uses the workbench to test two alternatives and consults the test dataset to interpret a difference she found. She preserves her formulation and declares dependency on those resources, referencing external materials and reports she can legitimately reference. She need not invent a laboratory Appoint or attribute protocol adoption to it.
Davi uses the same infrastructure in another project. A dataset result helps discard a material before ordering a prototype. His work takes another direction and has not generated a sale. He issues a reputational Nod referencing the external contribution and describing the consequence he received.
After completing her service, Beatriz recognizes that workbench and test access allowed investigation of a difficulty she could not examine with her workshop's resources. In addition to the previously agreed usage fee, she chooses an external transfer in recognition of that contribution. Her monetary Nod declares the amount already transferred and references the laboratory's work. The earlier fee and additional recognition have their own documents; the protocol neither calculates them nor determines their legal or tax treatment.
Beatriz's and Davi's Nods supply different information. One describes a consequence without a transfer; the other also declares an amount transferred. Neither establishes a universal share of results belonging to infrastructure. The laboratory gains no authority over users' work by appearing in its genealogy.
With necessary authorizations, Teresa examines the available accounts alongside income, expenses and maintenance needs. They help describe uses not captured solely by counting workbench hours. The collection remains incomplete: some users may keep private records or never record experiences, and a reference does not make their reports accessible.
In the fictional case, resources received still do not cover an equipment replacement. Teresa can present authorized information to potential supporters, revise the scope offered or seek other funding sources, respecting existing commitments. The laboratory's relevance to users and its financial condition need separate examination.
Computing infrastructure, a software library or a connectivity network could participate in similar relationships. Maintaining Legible is another possible contribution in this set. What deserves testing is whether knowing distributed consequences improves support and continuity decisions, considering the cost of recording, examining and maintaining that information.
Recognize the sources that supported the work too¶
Ana, Helena or Paula can recognize a consequence received from the specification, guides or tools they used. Ana, for example, can declare that the materials helped organize deliveries and recognitions by cycle. Her Traces and the pilot's files can support the explanation of actual use.
That Nod references the recognized contribution. It can point to an existing Appoint or to an external document or repository allowed by the format; there is no need to invent a record by the source's author. Separate recognition of distinct contributions uses distinct Nods.
Reading the materials or using the software requires neither a Nod nor payment; use follows the applicable licenses. A formal Appoint adopts the NRC identified in it. The convention concerns recognition when an adopter realizes economic value in an exchange transaction from a contribution declared under it; other consequences can also be recognized. One person's declaration does not oblige all other users to do the same.
Reading the examples and conditions of use¶
Each signature attributes the declaration to a key. The reader examines its
content, evidence and the authority of whoever declares on behalf of another
person or company. Each cycle's Nods identify the contributions recognized;
they need not form a chain between themselves. corrects is used to correct
an earlier Nod, not to mark the next stage of work.
Records can remain private. Sharing files, disclosing people's data and authorizing AI processing are separate decisions. Internal evidence remains subject to its access conditions. Preservation depends on the files and the care of those maintaining them.
Payment, contracting, employment relationships and tax documents follow the applicable acts, agreements and rules. The format neither replaces them nor determines their effects alone. A monetary Nod declares a transfer already made; it does not execute it. A reputational Nod can record a consequence without money. No record by itself requires offering the next stage of work.